User-assistance information at least partially based on an identified possible non-imaged portion of a skin

ABSTRACT

Described embodiments include a system, method, and program product. A described system includes a circuit that determines a substantial correspondence between a human-perceivable feature included in a border region segment of a selected medical skin image and a human-perceivable feature included in each other medical skin image of a plurality of medical skin images. A circuit gathers the determined substantial correspondences. A circuit generates data indicative of a border region-overlap status of the selected medical skin image. A circuit adds the data to an omitted-coverage list. A circuit iteratively designates a next medical skin image as the selected digital image, and initiates a processing of each of the iteratively designated next medical skin images. A circuit identifies a possible non-imaged portion of the region of interest. A circuit outputs user-assistance information based on the identified possible non-imaged portion of the skin.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is related to and claims the benefit of theearliest available effective filing date(s) from the following listedapplication(s) (the “Related Applications”) (e.g., claims earliestavailable priority dates for other than provisional patent applicationsor claims benefits under 35 USC §119(e) for provisional patentapplications, for any and all parent, grandparent, great-grandparent,etc. applications of the Related Application(s)).

RELATED APPLICATIONS

For purposes of the USPTO extra-statutory requirements, the presentapplication constitutes a continuation-in-part of U.S. patentapplication Ser. No. 13/374,002, entitled INFORMATIONAL DATA INDICATIVEOF A POSSIBLE NON-IMAGED PORTION OF A REGION OF INTEREST, namingRoderick A. Hyde, Jordin T. Kare, Eric C. Leuthardt, Erez Lieberman,Dennis J. Rivet, Elizabeth A. Sweeney, Lowell L. Wood, Jr., asinventors, filed Dec. 7, 2011, which is currently co-pending, or is anapplication of which a currently co-pending application is entitled tothe benefit of the filing date.

For purposes of the USPTO extra-statutory requirements, the presentapplication constitutes a continuation-in-part of U.S. patentapplication Ser. No. 13/374,000, entitled REPORTING INFORMATIONAL DATAINDICATIVE OF A POSSIBLE NON-IMAGED PORTION OF A REGION OF INTEREST,naming Roderick A. Hyde, Jordin T. Kare, Eric C. Leuthardt, ErezLieberman, Dennis J. Rivet, Elizabeth A. Sweeney, Lowell L. Wood, Jr.,as inventors, filed Dec. 7, 2011, which is currently co-pending, or isan application of which a currently co-pending application is entitledto the benefit of the filing date.

For purposes of the USPTO extra-statutory requirements, the presentapplication constitutes a continuation-in-part of U.S. patentapplication Ser. No. 13/374,005, entitled REPORTING INFORMATIONAL DATAINDICATIVE OF A POSSIBLE NON-IMAGED PORTION OF A SKIN, naming RoderickA. Hyde, Jordin T. Kare, Eric C. Leuthardt, Erez Lieberman, Dennis J.Rivet, Elizabeth A. Sweeney, Lowell L. Wood, Jr., as inventors, filedDec. 7, 2011, which is currently co-pending, or is an application ofwhich a currently co-pending application is entitled to the benefit ofthe filing date.

The United States Patent Office (USPTO) has published a notice to theeffect that the USPTO's computer programs require that patent applicantsreference both a serial number and indicate whether an application is acontinuation or continuation-in-part. Stephen G. Kunin, Benefit ofPrior-Filed Application, USPTO Official Gazette Mar. 18, 2003. Thepresent Applicant Entity (hereinafter “Applicant”) has provided above aspecific reference to the application(s) from which priority is beingclaimed as recited by statute. Applicant understands that the statute isunambiguous in its specific reference language and does not requireeither a serial number or any characterization, such as “continuation”or “continuation-in-part,” for claiming priority to U.S. patentapplications. Notwithstanding the foregoing, Applicant understands thatthe USPTO's computer programs have certain data entry requirements, andhence Applicant is designating the present application as acontinuation-in-part of its parent applications as set forth above, butexpressly points out that such designations are not to be construed inany way as any type of commentary or admission as to whether or not thepresent application contains any new matter in addition to the matter ofits parent application(s).

All subject matter of the Related Applications and of any and allparent, grandparent, great-grandparent, etc. applications of the RelatedApplications is incorporated herein by reference to the extent suchsubject matter is not inconsistent herewith.

SUMMARY

An example of an embodiment of environment 200 of FIG. 3 in use mayinclude determining whether the plurality of digital images 210 coversthe entire region of interest 202 of the surface 201, or whether thereare any possible non-imaged portions of the region of interest that arenot covered by the plurality of digital images. This may be useful whena surface has been imaged from several different locations rather thanimaged from a relatively fixed or known location such as by satellite oraerial photography. Examples of imaging a surface from several differentlocations may include examining a surface of an object for perceivabledefects, such as missing protective tiles on a spacecraft, or whenexamining the skin of a person or the surface of an internal organ of aperson for diseases, conditions, or changes over time. It is anticipatedthat a person or machine examining a surface would like to know whetherthe plurality of digital images covers the entire region of interest ofthe surface, or whether there are possible non-imaged portions of theregion of interest. It is further anticipated that a person or machineexamining such a surface would like to know where any possiblenon-imaged portions of the region of interest are located so that theexamination may be adjusted for that fact, or so that additional digitalimages of possible non-imaged portions of the region of interest may beacquired.

This example of the environment 200 in use includes, without limitation,an embodiment of the system 220 in use. In this example, the systemincludes an image receiver circuit 222 configured to receive theplurality of digital images 210. The plurality of digital images eachincludes a respective portion of the region of interest 202 of thesurface 201. See FIG. 6. For example, the surface may include the skinof a person's back, or the lining of a person's stomach. To lay theground work for determining whether there is possible non-imaged portion218 of the region of interest of the surface in the plurality of digitalimages, the system finds at least one respective perceivable featurelocated anywhere in the field of view for each of the plurality ofdigital images, including the border regions of the digital images. Tothis end, the system includes a feature-detection circuit 224 configuredto extract at least one perceivable feature included in each digitalimage of the plurality of digital images. For example, where the surfaceis the skin, an extracted perceivable feature may include a mole, awrinkle, a fold, a human-vision perceivable discontinuity, a hairpattern, or a vein. The system includes a border region detectioncircuit 226 configured to detect a border region segment of a digitalimage. The dimensions of the border region segment may be selected forexample as is appropriate for the resolution of digital images includedin the plurality of digital images and the processing power of thesystem.

In this example of the system 220 in use, the system looks to see ifthere is a common perceivable feature included in both a border regionsegment of a selected digital image and in another digital image of theplurality of digital images. If there is no common perceivable feature,the system reports a possible non-imaged portion of the region ofinterest. For example, see FIGS. 5 and 6. In this regard, afeature-matching circuit 228 of the system looks for a commonperceivable feature in both a border region segment of a selecteddigital image and anywhere in the field of view of another digital imageof the plurality of digital images. The system accomplishes this bydetermining if a substantial correspondence exists between (x) aperceivable feature included in a border region segment of the selecteddigital image of the plurality of digital images and (y) at least onerespective perceivable feature included in each digital image of theplurality of digital images other than the selected digital image. Forexample, the feature matching circuit may output a “0” if no substantialcorrespondence is found, and output a “1” if a substantialcorrespondence is found. In an embodiment, the system proceeds aroundthe several border regions of the selected digital image and similarlydetermine a substantial correspondence for each respective featureincluded in the several border regions with respect to each digitalimage of the plurality of digital images other than the selected digitalimage. The system includes a data collection circuit 232 configured togather the determined substantial correspondence in the form of “1” and“0” for the perceivable feature included in the border region segment ofthe selected digital image.

In this example of the system 220 in use, the system includes areporting circuit 236 configured to output informational data indicativeof a possible non-imaged portion of the region of interest adjacent tothe selected digital image. The informational data is responsive to anabsence of a determined substantial correspondence (all 0's) between theperceivable feature included in the border region segment of theselected digital image and at least one respective perceivable featureincluded in each digital image of the plurality of digital images otherthan the selected digital image. For example, the system in generatingthe informational data treats a determination of an absence ofsubstantial correspondence (all 0's) for the perceivable feature of theborder region segment of the selected digital image as an indicationthat there likely is no border region overlap with any other feature ofthe remaining digital images and outputs that there is a possibleadjacent non-imaged portion. For example, the system in generating theinformational data treats a determination of a substantialcorrespondence (at least a single 1) for the perceivable feature of theborder region segment of the selected digital image as an indicationthat there likely is a possible border region overlap with at least onedetected border region feature of the remaining digital images,concludes the adjacent portion is likely imaged, and does not outputthat there is a possible adjacent non-imaged portion.

For example, and without limitation, an embodiment of the subject matterdescribed herein includes a system. In this embodiment, the systemincludes a feature-detection circuit configured to extract at least onerespective human-perceivable feature included in each medical image of aplurality of medical images of the skin of an individual human(hereafter “medical skin images”). The each medical image of pluralityof medical skin images includes a respective portion of a region ofinterest of a surface of the skin of the individual human, and wasacquired by a handheld digital image acquisition device. The systemincludes a feature matching circuit configured to determine asubstantial correspondence between (x) an extracted human-perceivablefeature included in a border region segment of a selected medical skinimage of the plurality of medical skin images and (y) an extracted atleast one respective human-perceivable feature included in the eachmedical skin image of the plurality of medical skin images other thanthe selected medical skin image. The system includes a data collectioncircuit configured to gather the determined substantial correspondencesfor the extracted human-perceivable feature included in the borderregion segment of the selected medical skin image. The system includesan overlap-analysis circuit configured to generate data indicative of aborder region-overlap status of the selected medical skin image. Thedata is generated at least partially in response to the determinedsubstantial correspondences. The system includes a list managementcircuit configured to add the data indicative of the determined borderregion-overlap status for the border region segment of the selectedmedical skin image to an omitted-coverage list. The system includes aniteration control circuit configured to iteratively designate a nextmedical skin image from the plurality of medical skin images as theselected medical skin image until each medical skin image of theplurality of medical skin images has been designated. The iterationcontrol circuit is also configured to initiate a processing of each ofthe iteratively designated next medical skin images by thefeature-matching circuit, the data collection circuit, theoverlap-analysis circuit, and the list management circuit. The systemincludes a coverage-analysis circuit configured to identify a particularportion of the skin surface as likely not included in the plurality ofmedical skin images (hereafter “possible non-imaged portion of theregion of interest”). The identifying the possible non-imaged portion ofthe region of interest at least partially based on the omitted-coveragelist. The system also includes (h) a reporting circuit configured tooutput user-assistance information at least partially based on theidentified possible non-imaged portion of the skin.

In an embodiment, the system includes an image receiver circuitconfigured to receive the plurality of medical skin images. In anembodiment, the system includes a border region detection circuitconfigured to detect a border region segment of a medical skin image ofthe plurality of medical skin images. In an embodiment, the systemincludes computer-readable media configured to maintain theuser-assistance information corresponding to the identified possiblenon-imaged portion of the region of interest and to the signpost medicalskin image. In an embodiment, the system includes a communicationsdevice configured to display a particular human-perceivable depiction ofthe user-assistance information.

For example, and without limitation, an embodiment of the subject matterdescribed herein includes a method implemented in a computing device. Inthis embodiment, the method includes an operation (a) extracting atleast one respective human-perceivable feature included in each medicalimage of a plurality of medical images of the skin of an individualhuman (hereafter “medical skin images”). The each medical image ofplurality of medical skin images includes a respective portion of aregion of interest of a surface of the skin of the individual human, andwas acquired by a handheld digital image acquisition device. The methodincludes an operation (b) determining a substantial correspondencebetween (x) an extracted human-perceivable feature included in a borderregion segment of a selected medical skin image of the plurality ofmedical skin images and (y) an extracted at least one respectivehuman-perceivable feature included in each medical skin image of theplurality of medical skin images other than the selected medical skinimage. The method includes an operation (c) gathering the determinedsubstantial correspondences for the human-perceivable feature includedin the border region segment of the selected medical skin image. Themethod includes an operation (d) generating data indicative of a borderregion-overlap status of the selected medical skin image. The data isgenerated at least partially in response to the determined substantialcorrespondences. The method includes an operation (e) adding the dataindicative of the determined border region-overlap status for the borderregion segment of the selected medical skin image to an omitted-coveragelist. The method includes an operation (f) iteratively designating anext medical skin image from the plurality of medical skin images as theselected medical skin image until each medical skin image of theplurality of medical skin images has been designated. The methodincludes an operation (g) processing of each of the iterativelydesignated next medical skin images, the processing includes operations(b), (c), (d), and (e). The method includes an operation (h) identifyinga particular portion of the skin surface as likely not included in theplurality of medical skin images (hereafter “possible non-imaged portionof the skin”). The identifying the possible non-imaged portion of theskin is at least partially based on the omitted-coverage list. Themethod includes an operation (i) outputting user-assistance informationat least partially based on the identified possible non-imaged portionof the skin.

In an embodiment, the method includes receiving the plurality of medicalskin images. In an embodiment, the method includes detecting a borderregion segment of a medical skin image of the plurality of medical skinimages. In an embodiment, the method includes maintaining theuser-assistance information in computer-readable storage media.

For example, and without limitation, an embodiment of the subject matterdescribed herein includes a computer program product. In thisembodiment, the computer program product includes computer-readablemedia bearing program instructions. The program instructions, whenexecuted by a processor of a computing device, cause the computingdevice to perform a process. The process includes an operation (i)extracting at least one respective human-perceivable feature included ineach medical image of a plurality of medical images of the skin of anindividual human (hereafter “medical skin images”). The each medicalimage of plurality of medical skin images includes a respective portionof a region of interest of a surface of the skin of the individualhuman, and was acquired by a handheld digital image acquisition device.The process includes an operation (ii) determining a substantialcorrespondence between (x) an extracted human-perceivable featureincluded in a border region segment of a selected medical skin image ofthe plurality of medical skin images and (y) an extracted at least onerespective human-perceivable feature included in each medical skin imageof the plurality of medical skin images other than the selected medicalskin image. The process includes an operation (iii) gathering thedetermined substantial correspondences for the human-perceivable featureincluded in the border region segment of the selected medical skinimage. The process includes an operation (iv) generating data indicativeof a border region-overlap status of the selected medical skin image.The data is generated at least partially in response to the determinedsubstantial correspondences. The process includes an operation (v)adding the data indicative of the determined border region-overlapstatus for the border region segment of the selected medical skin imageto an omitted-coverage list. The process includes an operation (vi)iteratively designating a next medical skin image from the plurality ofmedical skin images as the selected medical skin image until eachmedical skin image of the plurality of medical skin images has beendesignated. The process includes an operation (vii) processing of eachof the iteratively designated next medical skin images, the processingincludes operations (ii), (iii), (iv), and (v). The process includes anoperation (viii) identifying a particular portion of the skin surface aslikely not included in the plurality of medical skin images (hereafter“possible non-imaged portion of the skin”). The identifying the possiblenon-imaged portion of the skin is at least partially based on theomitted-coverage list. The process includes an operation (ix) outputtinguser-assistance information at least partially based on the identifiedpossible non-imaged portion of the skin.

In an embodiment, the process includes receiving the plurality ofmedical skin images. In an embodiment, the process includes detecting aborder region segment of a medical skin image of the plurality ofmedical skin images. In an embodiment, the process includes displayingthe user-assistance information. In an embodiment, the process includesmaintaining the user-assistance information in computer-readable storagemedia. In an embodiment, the computer-readable media includes tangiblecomputer-readable media. In an embodiment, the computer-readable mediaincludes communications media.

For example, and without limitation, an embodiment of the subject matterdescribed herein includes a system. In this embodiment, the systemincludes (a) means for extracting at least one respectivehuman-perceivable feature included in each medical image of a pluralityof medical images of the skin of an individual human (hereafter “medicalskin images”). The each medical image of plurality of medical skinimages includes a respective portion of a region of interest of asurface of the skin of the individual human, and was acquired by ahandheld digital image acquisition device. The system includes (b) meansfor determining a substantial correspondence between (x) an extractedhuman-perceivable feature included in a border region segment of aselected medical skin image of the plurality of medical skin images and(y) an extracted at least one respective human-perceivable featureincluded in each medical skin image of the plurality of medical skinimages other than the selected medical skin image. The system includes(c) means for gathering the determined substantial correspondences forthe extracted human-perceivable feature included in the border regionsegment of the selected medical skin image. The system includes (d)means for generating data indicative of a border region-overlap statusof the selected medical skin image. The data is generated at leastpartially in response to the determined substantial correspondences. Thesystem includes (e) means for adding the data indicative of thedetermined border region-overlap status for the border region segment ofthe selected medical skin image to an omitted-coverage list. The systemincludes (f) means for iteratively designating a next medical skin imagefrom the plurality of medical skin images as the selected medical skinimage until each medical skin image of the plurality of medical skinimages has been designated. The system includes (g) means for initiatinga processing of each of the iteratively designated next medical skinimages, the processing includes operations at means (b), (c), (d), and(e). The system includes (h) means for identifying a particular portionof the skin surface as likely not included in the plurality of medicalskin images (hereafter “possible non-imaged portion of the skin”). Theidentifying the possible non-imaged portion of the skin is at leastpartially based on the omitted-coverage list. The system includes (i)means for outputting user-assistance information at least partiallybased on the identified possible non-imaged portion of the skin.

The foregoing summary is illustrative only and is not intended to be inany way limiting. In addition to the illustrative aspects, embodiments,and features described above, further aspects, embodiments, and featureswill become apparent by reference to the drawings and the followingdetailed description.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an example embodiment of a thin computing device inwhich embodiments may be implemented;

FIG. 2 illustrates an example embodiment of a general-purpose computingsystem in which embodiments may be implemented;

FIG. 3 illustrates an example environment in which embodiments may beimplemented;

FIG. 4 illustrates an example digital image of the plurality of digitalimages;

FIG. 5 illustrates an example of certain digital images of the pluralityof digital images;

FIG. 6 illustrates an example of certain digital images of the pluralityof digital images;

FIG. 7 illustrates an example operational flow;

FIG. 8 illustrates an alternative embodiment of the example operationalflow of FIG. 7;

FIG. 9 illustrates an alternative embodiment of the example operationalflow of FIG. 7;

FIG. 10 illustrates an example computer program product;

FIG. 11 illustrates an example system;

FIG. 12 illustrates an example environment;

FIG. 13 partially illustrates an application of an alternativeembodiment of the coverage-analysis circuit to the plurality of digitalimages previously illustrated in FIG. 6;

FIG. 14 illustrates an example operational flow;

FIG. 15 illustrates an alternative embodiment of the example of theoperational flow of FIG. 14;

FIG. 16 illustrates an alternative embodiment of the example of theoperational flow of FIG. 14;

FIG. 17 illustrates an example computer program product;

FIG. 18 illustrates an example system;

FIG. 19 illustrates an environment;

FIG. 20 illustrates a handheld digital image acquisition device;

FIG. 21 illustrates an example operational flow;

FIG. 22 illustrates an alternative embodiment of the operational flow ofFIG. 21;

FIG. 23 illustrates an alternative embodiment of the operational flow ofFIG. 21;

FIG. 24 illustrates an alternative embodiment of the operational flow ofFIG. 21;

FIG. 25 illustrates an example computer program product;

FIG. 26 illustrates an alternative embodiment of the computer programproduct of FIG. 25;

FIG. 27 illustrates an example system;

FIG. 28 illustrates an example environment;

FIG. 29 illustrates an example operational flow;

FIG. 30 illustrates an alternative embodiment of the operational flow ofFIG. 29;

FIG. 31 illustrates an example computer program product;

FIG. 32 illustrates an alternative embodiment of the computer programproduct of FIG. 31; and

FIG. 33 illustrates an example system.

DETAILED DESCRIPTION

In the following detailed description, reference is made to theaccompanying drawings, which form a part hereof. In the drawings,similar symbols typically identify similar components, unless contextdictates otherwise. The illustrated embodiments described in thedetailed description, drawings, and claims are not meant to be limiting.Other embodiments may be utilized, and other changes may be made,without departing from the spirit or scope of the subject matterpresented here.

Those having skill in the art will recognize that the state of the arthas progressed to the point where there is little distinction leftbetween hardware, software, and/or firmware implementations of aspectsof systems; the use of hardware, software, and/or firmware is generally(but not always, in that in certain contexts the choice between hardwareand software can become significant) a design choice representing costvs. efficiency tradeoffs. Those having skill in the art will appreciatethat there are various vehicles by which processes and/or systems and/orother technologies described herein can be effected (e.g., hardware,software, and/or firmware), and that the preferred vehicle will varywith the context in which the processes and/or systems and/or othertechnologies are deployed. For example, if an implementer determinesthat speed and accuracy are paramount, the implementer may opt for amainly hardware and/or firmware vehicle; alternatively, if flexibilityis paramount, the implementer may opt for a mainly softwareimplementation; or, yet again alternatively, the implementer may opt forsome combination of hardware, software, and/or firmware. Hence, thereare several possible vehicles by which the processes and/or devicesand/or other technologies described herein may be effected, none ofwhich is inherently superior to the other in that any vehicle to beutilized is a choice dependent upon the context in which the vehiclewill be deployed and the specific concerns (e.g., speed, flexibility, orpredictability) of the implementer, any of which may vary. Those skilledin the art will recognize that optical aspects of implementations willtypically employ optically-oriented hardware, software, and or firmware.

In some implementations described herein, logic and similarimplementations may include software or other control structuressuitable to operation. Electronic circuitry, for example, may manifestone or more paths of electrical current constructed and arranged toimplement various logic functions as described herein. In someimplementations, one or more media are configured to bear adevice-detectable implementation if such media hold or transmit aspecial-purpose device instruction set operable to perform as describedherein. In some variants, for example, this may manifest as an update orother modification of existing software or firmware, or of gate arraysor other programmable hardware, such as by performing a reception of ora transmission of one or more instructions in relation to one or moreoperations described herein. Alternatively or additionally, in somevariants, an implementation may include special-purpose hardware,software, firmware components, and/or general-purpose componentsexecuting or otherwise invoking special-purpose components.Specifications or other implementations may be transmitted by one ormore instances of tangible transmission media as described herein,optionally by packet transmission or otherwise by passing throughdistributed media at various times.

Alternatively or additionally, implementations may include executing aspecial-purpose instruction sequence or otherwise invoking circuitry forenabling, triggering, coordinating, requesting, or otherwise causing oneor more occurrences of any functional operations described below. Insome variants, operational or other logical descriptions herein may beexpressed directly as source code and compiled or otherwise invoked asan executable instruction sequence. In some contexts, for example, C++or other code sequences can be compiled directly or otherwiseimplemented in high-level descriptor languages (e.g., alogic-synthesizable language, a hardware description language, ahardware design simulation, and/or other such similar mode(s) ofexpression). Alternatively or additionally, some or all of the logicalexpression may be manifested as a Verilog-type hardware description orother circuitry model before physical implementation in hardware,especially for basic operations or timing-critical applications. Thoseskilled in the art will recognize how to obtain, configure, and optimizesuitable transmission or computational elements, material supplies,actuators, or other common structures in light of these teachings.

In a general sense, those skilled in the art will recognize that thevarious embodiments described herein can be implemented, individuallyand/or collectively, by various types of electro-mechanical systemshaving a wide range of electrical components such as hardware, software,firmware, and/or virtually any combination thereof; and a wide range ofcomponents that may impart mechanical force or motion such as rigidbodies, spring or torsional bodies, hydraulics, electro-magneticallyactuated devices, and/or virtually any combination thereof.Consequently, as used herein “electro-mechanical system” includes, butis not limited to, electrical circuitry operably coupled with atransducer (e.g., an actuator, a motor, a piezoelectric crystal, a MicroElectro Mechanical System (MEMS), etc.), electrical circuitry having atleast one discrete electrical circuit, electrical circuitry having atleast one integrated circuit, electrical circuitry having at least oneapplication specific integrated circuit, electrical circuitry forming ageneral purpose computing device configured by a computer program (e.g.,a general purpose computer configured by a computer program which atleast partially carries out processes and/or devices described herein,or a microprocessor configured by a computer program which at leastpartially carries out processes and/or devices described herein),electrical circuitry forming a memory device (e.g., forms of memory(e.g., random access, flash, read only, etc.)), electrical circuitryforming a communications device (e.g., a modem, communications switch,optical-electrical equipment, etc.), and/or any non-electrical analogthereto, such as optical or other analogs. Those skilled in the art willalso appreciate that examples of electro-mechanical systems include butare not limited to a variety of consumer electronics systems, medicaldevices, as well as other systems such as motorized transport systems,factory automation systems, security systems, and/orcommunication/computing systems. Those skilled in the art will recognizethat electro-mechanical as used herein is not necessarily limited to asystem that has both electrical and mechanical actuation except ascontext may dictate otherwise.

In a general sense, those skilled in the art will also recognize thatthe various aspects described herein which can be implemented,individually and/or collectively, by a wide range of hardware, software,firmware, and/or any combination thereof can be viewed as being composedof various types of “electrical circuitry.” Consequently, as used herein“electrical circuitry” includes, but is not limited to, electricalcircuitry having at least one discrete electrical circuit, electricalcircuitry having at least one integrated circuit, electrical circuitryhaving at least one application specific integrated circuit, electricalcircuitry forming a general purpose computing device configured by acomputer program (e.g., a general purpose computer configured by acomputer program which at least partially carries out processes and/ofdevices described herein, or a microprocessor configured by a computerprogram which at least partially carries out processes and/or devicesdescribed herein), electrical circuitry forming a memory device (e.g.,forms of memory (e.g., random access, flash, read only, etc.)), and/orelectrical circuitry forming a communications device (e.g., a modem,communications switch, optical-electrical equipment, etc.). Those havingskill in the art will recognize that the subject matter described hereinmay be implemented in an analog or digital fashion or some combinationthereof.

Those skilled in the art will further recognize that at least a portionof the devices and/or processes described herein can be integrated intoan image processing system. A typical image processing system maygenerally include one or more of a system unit housing, a video displaydevice, memory such as volatile or non-volatile memory, processors suchas microprocessors or digital signal processors, computational entitiessuch as operating systems, drivers, applications programs, one or moreinteraction devices (e.g., a touch pad, a touch screen, an antenna,etc.), control systems including feedback loops and control motors(e.g., feedback for sensing lens position and/or velocity; controlmotors for moving/distorting lenses to give desired focuses). An imageprocessing system may be implemented utilizing suitable commerciallyavailable components, such as those typically found in digital stillsystems and/or digital motion systems.

Those skilled in the art will likewise recognize that at least some ofthe devices and/or processes described herein can be integrated into adata processing system. Those having skill in the art will recognizethat a data processing system generally includes one or more of a systemunit housing, a video display device, memory such as volatile ornon-volatile memory, processors such as microprocessors or digitalsignal processors, computational entities such as operating systems,drivers, graphical user interfaces, and applications programs, one ormore interaction devices (e.g., a touch pad, a touch screen, an antenna,etc.), and/or control systems including feedback loops and controlmotors (e.g., feedback for sensing position and/or velocity; controlmotors for moving and/or adjusting components and/or quantities). A dataprocessing system may be implemented utilizing suitable commerciallyavailable components, such as those typically found in datacomputing/communication and/or network computing/communication systems.

FIGS. 1 and 2 provide respective general descriptions of severalenvironments in which implementations may be implemented. FIG. 1 isgenerally directed toward a thin computing environment 19 having a thincomputing device 20, and FIG. 2 is generally directed toward a generalpurpose computing environment 100 having general purpose computingdevice 110. However, as prices of computer components drop and ascapacity and speeds increase, there is not always a bright line betweena thin computing device and a general purpose computing device. Further,there is a continuous stream of new ideas and applications forenvironments benefited by use of computing power. As a result, nothingshould be construed to limit disclosed subject matter herein to aspecific computing environment unless limited by express language.

FIG. 1 and the following discussion are intended to provide a brief,general description of a thin computing environment 19 in whichembodiments may be implemented. FIG. 1 illustrates an example systemthat includes a thin computing device 20, which may be included orembedded in an electronic device that also includes a device functionalelement 50. For example, the electronic device may include any itemhaving electrical or electronic components playing a role in afunctionality of the item, such as for example, a refrigerator, a car, adigital image acquisition device, a camera, a cable modem, a printer anultrasound device, an x-ray machine, a non-invasive imaging device, oran airplane. For example, the electronic device may include any itemthat interfaces with or controls a functional element of the item. Inanother example, the thin computing device may be included in animplantable medical apparatus or device. In a further example, the thincomputing device may be operable to communicate with an implantable orimplanted medical apparatus. For example, a thin computing device mayinclude a computing device having limited resources or limitedprocessing capability, such as a limited resource computing device, awireless communication device, a mobile wireless communication device, asmart phone, an electronic pen, a handheld electronic writing device, ascanner, a cell phone, a smart phone (such as an Android® or iPhone®based device), a tablet device (such as an iPad®) or a Blackberry®device. For example, a thin computing device may include a thin clientdevice or a mobile thin client device, such as a smart phone, tablet,notebook, or desktop hardware configured to function in a virtualizedenvironment.

The thin computing device 20 includes a processing unit 21, a systemmemory 22, and a system bus 23 that couples various system componentsincluding the system memory 22 to the processing unit 21. The system bus23 may be any of several types of bus structures including a memory busor memory controller, a peripheral bus, and a local bus using any of avariety of bus architectures. The system memory includes read-onlymemory (ROM) 24 and random access memory (RAM) 25. A basic input/outputsystem (BIOS) 26, containing the basic routines that help to transferinformation between sub-components within the thin computing device 20,such as during start-up, is stored in the ROM 24. A number of programmodules may be stored in the ROM 24 or RAM 25, including an operatingsystem 28, one or more application programs 29, other program modules 30and program data 31.

A user may enter commands and information into the computing device 20through one or more input interfaces. An input interface may include atouch-sensitive display, or one or more switches or buttons withsuitable input detection circuitry. A touch-sensitive display isillustrated as a display 32 and screen input detector 33. One or moreswitches or buttons are illustrated as hardware buttons 44 connected tothe system via a hardware button interface 45. The output circuitry ofthe touch-sensitive display 32 is connected to the system bus 23 via avideo driver 37. Other input devices may include a microphone 34connected through a suitable audio interface 35, or a physical hardwarekeyboard (not shown). Output devices may include the display 32, or aprojector display 36.

In addition to the display 32, the computing device 20 may include otherperipheral output devices, such as at least one speaker 38. Otherexternal input or output devices 39, such as a joystick, game pad,satellite dish, scanner or the like may be connected to the processingunit 21 through a USB port 40 and USB port interface 41, to the systembus 23. Alternatively, the other external input and output devices 39may be connected by other interfaces, such as a parallel port, game portor other port. The computing device 20 may further include or be capableof connecting to a flash card memory (not shown) through an appropriateconnection port (not shown). The computing device 20 may further includeor be capable of connecting with a network through a network port 42 andnetwork interface 43, and through wireless port 46 and correspondingwireless interface 47 may be provided to facilitate communication withother peripheral devices, including other computers, printers, and so on(not shown). It will be appreciated that the various components andconnections shown are examples and other components and means ofestablishing communication links may be used.

The computing device 20 may be primarily designed to include a userinterface. The user interface may include a character, a key-based, oranother user data input via the touch sensitive display 32. The userinterface may include using a stylus (not shown). Moreover, the userinterface is not limited to an actual touch-sensitive panel arranged fordirectly receiving input, but may alternatively or in addition respondto another input device such as the microphone 34. For example, spokenwords may be received at the microphone 34 and recognized.Alternatively, the computing device 20 may be designed to include a userinterface having a physical keyboard (not shown).

The device functional elements 50 are typically application specific andrelated to a function of the electronic device, and are coupled with thesystem bus 23 through an interface (not shown). The functional elementsmay typically perform a single well-defined task with little or no userconfiguration or setup, such as a refrigerator keeping food cold, a cellphone connecting with an appropriate tower and transceiving voice ordata information, a camera capturing and saving an image, orcommunicating with an implantable medical apparatus.

In certain instances, one or more elements of the thin computing device20 may be deemed not necessary and omitted. In other instances, one ormore other elements may be deemed necessary and added to the thincomputing device.

FIG. 2 and the following discussion are intended to provide a brief,general description of an environment in which embodiments may beimplemented. FIG. 2 illustrates an example embodiment of ageneral-purpose computing system in which embodiments may beimplemented, shown as a computing system environment 100. Components ofthe computing system environment 100 may include, but are not limitedto, a general purpose computing device 110 having a processor 120, asystem memory 130, and a system bus 121 that couples various systemcomponents including the system memory to the processor 120. The systembus 121 may be any of several types of bus structures including a memorybus or memory controller, a peripheral bus, and a local bus using any ofa variety of bus architectures. By way of example, and not limitation,such architectures include Industry Standard Architecture (ISA) bus,Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, VideoElectronics Standards Association (VESA) local bus, and PeripheralComponent Interconnect (PCI) bus, also known as Mezzanine bus.

The computing system environment 100 typically includes a variety ofcomputer-readable media products. Computer-readable media may includeany media that can be accessed by the computing device 110 and includeboth volatile and nonvolatile media, removable and non-removable media.By way of example, and not of limitation, computer-readable media mayinclude computer storage media. By way of further example, and not oflimitation, computer-readable media may include a communication media.

Computer storage media includes volatile and nonvolatile, removable andnon-removable media implemented in any method or technology for storageof information such as computer-readable instructions, data structures,program modules, or other data. Computer storage media includes, but isnot limited to, random-access memory (RAM), read-only memory (ROM),electrically erasable programmable read-only memory (EEPROM), flashmemory, or other memory technology, CD-ROM, digital versatile disks(DVD), or other optical disk storage, magnetic cassettes, magnetic tape,magnetic disk storage, or other magnetic storage devices, or any othermedium which can be used to store the desired information and which canbe accessed by the computing device 110. In a further embodiment, acomputer storage media may include a group of computer storage mediadevices. In another embodiment, a computer storage media may include aninformation store. In another embodiment, an information store mayinclude a quantum memory, a photonic quantum memory, or atomic quantummemory. Combinations of any of the above may also be included within thescope of computer-readable media.

Communication media may typically embody computer-readable instructions,data structures, program modules, or other data in a modulated datasignal such as a carrier wave or other transport mechanism and includeany information delivery media. The term “modulated data signal” means asignal that has one or more of its characteristics set or changed insuch a manner as to encode information in the signal. By way of example,and not limitation, communications media may include wired media, suchas a wired network and a direct-wired connection, and wireless mediasuch as acoustic, RF, optical, and infrared media.

The system memory 130 includes computer storage media in the form ofvolatile and nonvolatile memory such as ROM 131 and RAM 132. A RAM mayinclude at least one of a DRAM, an EDO DRAM, a SDRAM, a RDRAM, a VRAM,or a DDR DRAM. A basic input/output system (BIOS) 133, containing thebasic routines that help to transfer information between elements withinthe computing device 110, such as during start-up, is typically storedin ROM 131. RAM 132 typically contains data and program modules that areimmediately accessible to or presently being operated on by theprocessor 120. By way of example, and not limitation, FIG. 2 illustratesan operating system 134, application programs 135, other program modules136, and program data 137. Often, the operating system 134 offersservices to applications programs 135 by way of one or more applicationprogramming interfaces (APIs) (not shown). Because the operating system134 incorporates these services, developers of applications programs 135need not redevelop code to use the services. Examples of APIs providedby operating systems such as Microsoft's “WINDOWS”® are well known inthe art.

The computing device 110 may also include other removable/non-removable,volatile/nonvolatile computer storage media products. By way of exampleonly, FIG. 2 illustrates a non-removable non-volatile memory interface(hard disk interface) 140 that reads from and writes for example tonon-removable, non-volatile magnetic media. FIG. 2 also illustrates aremovable non-volatile memory interface 150 that, for example, iscoupled to a magnetic disk drive 151 that reads from and writes to aremovable, non-volatile magnetic disk 152, or is coupled to an opticaldisk drive 155 that reads from and writes to a removable, non-volatileoptical disk 156, such as a CD ROM. Other removable/nonremovable,volatile/non-volatile computer storage media that can be used in theexample operating environment include, but are not limited to, magnetictape cassettes, memory cards, flash memory cards, DVDs, digital videotape, solid state RAM, and solid state ROM. The hard disk drive 141 istypically connected to the system bus 121 through a non-removable memoryinterface, such as the interface 140, and magnetic disk drive 151 andoptical disk drive 155 are typically connected to the system bus 121 bya removable non-volatile memory interface, such as interface 150.

The drives and their associated computer storage media discussed aboveand illustrated in FIG. 2 provide storage of computer-readableinstructions, data structures, program modules, and other data for thecomputing device 110. In FIG. 2, for example, hard disk drive 141 isillustrated as storing an operating system 144, application programs145, other program modules 146, and program data 147. Note that thesecomponents can either be the same as or different from the operatingsystem 134, application programs 135, other program modules 136, andprogram data 137. The operating system 144, application programs 145,other program modules 146, and program data 147 are given differentnumbers here to illustrate that, at a minimum, they are differentcopies.

A user may enter commands and information into the computing device 110through input devices such as a microphone 163, keyboard 162, andpointing device 161, commonly referred to as a mouse, trackball, ortouch pad. Other input devices (not shown) may include at least one of atouch sensitive display, joystick, game pad, satellite dish, andscanner. These and other input devices are often connected to theprocessor 120 through a user input interface 160 that is coupled to thesystem bus, but may be connected by other interface and bus structures,such as a parallel port, game port, or a universal serial bus (USB).

A display 191, such as a monitor or other type of display device orsurface may be connected to the system bus 121 via an interface, such asa video interface 190. A projector display engine 192 that includes aprojecting element may be coupled to the system bus. In addition to thedisplay, the computing device 110 may also include other peripheraloutput devices such as speakers 197 and printer 196, which may beconnected through an output peripheral interface 195.

The computing system environment 100 may operate in a networkedenvironment using logical connections to one or more remote computers,such as a remote computer 180. The remote computer 180 may be a personalcomputer, a server, a router, a network PC, a peer device, or othercommon network node, and typically includes many or all of the elementsdescribed above relative to the computing device 110, although only amemory storage device 181 has been illustrated in FIG. 2. The networklogical connections depicted in FIG. 2 include a local area network(LAN) and a wide area network (WAN), and may also include other networkssuch as a personal area network (PAN) (not shown). Such networkingenvironments are commonplace in offices, enterprise-wide computernetworks, intranets, and the Internet.

When used in a networking environment, the computing system environment100 is connected to the network 171 through a network interface, such asthe network interface 170, the modem 172, or the wireless interface 193.The network may include a LAN network environment, or a WAN networkenvironment, such as the Internet. In a networked environment, programmodules depicted relative to the computing device 110, or portionsthereof, may be stored in a remote memory storage device. By way ofexample, and not limitation, FIG. 2 illustrates remote applicationprograms 185 as residing on memory storage device 181. It will beappreciated that the network connections shown are examples and othermeans of establishing communication link between the computers may beused.

In certain instances, one or more elements of the computing device 110may be deemed not necessary and omitted. In other instances, one or moreother elements may be deemed necessary and added to the computingdevice.

FIG. 3 illustrates an example environment 200 in which embodiments maybe implemented. The environment includes a surface 201, a digital imageacquisition device 205 (illustrated as a camera), a plurality of digitalimages 210, a system 220, and a computing device 292 having a screen 294visible to a person 296. In an embodiment, two or more of the devices ofthe environment may communicate wirelessly with each other. In anotherembodiment, two or more of the devices of the environment maycommunicate via wired link.

FIGS. 4-5 illustrate an example of the digital images 210. FIG. 4illustrates an example digital image 210.1 of the plurality of digitalimages 210. The digital image 210.1 includes perceivable features A-Nlocated in the field of view of the digital image 210.1. The field ofview of the digital image 210.1 includes a peripheral border region210.1B. The peripheral border region may be divided into at least twoborder region segments for image processing. The at least two borderregion segments are illustrated as border region segments 211.1 and211.2. The border segments may abut each other in an embodiment, but areillustrated in FIG. 4 as spaced apart for clarity. Each border regionsegment has a length (no reference number) and a width 212. The lengthand/or width of the at least two border segments may or may not beequal. Perceivable features A-J are also illustrated as located withinthe border region 210.1B of the digital image 210.1

FIG. 5 illustrates an example of digital images 210.1-210.4 of theplurality of digital images 210. Certain perceivable features ofperceivable features A-N are also illustrated as lying within the fieldof view of the digital images 210.2 and 210.4. For example, perceivablefeatures A and B lie with the field of view of the digital image 210.4,and perceivable features D and E lie within the field of view of thedigital image 210.2.

FIG. 6 illustrates an example of digital images 210.1-210.8 of theplurality of digital images 210. In this example, the digital images210.1-210.8 include respective portions of a region of interest 202 ofthe surface 201. FIG. 6 also illustrates a possible non-imaged portion218 of a region of interest 202 of the surface 201 as adjacent todigital images 210.3, 210.5, 210.6, and 210.7. FIG. 6 also illustratesdigital image 210.6 as including an example perceivable feature W. FIG.6 also illustrates an embodiment of a spatial relationship ororientation between the perceivable feature W and the possiblenon-imaged or unimaged portion 218 indicated by a line 216. In anembodiment, the line may be established perpendicular to an edge of thedigital image 210.6.

Returning to FIG. 3, the system 220 includes a feature-detection circuit224. The feature detection circuit is configured to extract at least onerespective perceivable feature included in each digital image of theplurality of digital images 210. The each digital image of the pluralityof digital images includes a respective portion of a region of interestof a surface a respective portion of the region of interest 202 of thesurface 201. An example circuit or system configured to extract at leastone respective perceivable feature included in each digital image of theplurality of digital images is provided by Photomodeler and PhotoModelerScanner products by PhotoModeler ® of Vancouver, BC, Canada.

For example, a perceivable feature may include a discernable shape. Forexample, a perceivable feature may be discernable under natural lightingor under a particular lighting, such as infrared lighting. For example,a perceivable feature may be a static perceivable feature of thesurface. For example, where the surface is a surface of a human skin, aperceivable feature may include a hair, wrinkle, surface, color,structure, or texture variation. For example, a perceivable feature mayinclude a color and/or texture change and/or shift in skin or tissuepigments (e.g., melanoma or other tumor borders, burns, scar tissue,necrotic tissue). For example, a perceivable feature may include aperceivable surface vascular feature of a cavity or lumen. For example,a perceivable feature may include a perceivable surface anomaly. Forexample, a perceivable feature may include a perceivable surfaceanatomical feature. For example, a perceivable feature may include aperceivable surface vascular feature. For example, a perceivable featuremay include a perceivable surface vessel, blood vessel, vascularstructure, or a pattern presented by one or more blood vessels of asurface of a human or animal. For example, a perceivable feature mayinclude a perceivable physical structure, void, border, component,tissue, structural feature, or density variation of a surface. Forexample, a perceivable feature may include a perceivable patternpresented by one or more features. For example, a perceivable featuremay include a perceivable fiducial formed by one or more structures,colors, or shapes of a surface. For example, a perceivable feature mayinclude a perceivable relative size or spatial relationship of two ormore perceivable physical structures, voids, borders, components,tissues, structural features, or density variations of a surface. Forexample, a perceivable feature may include a perceivable normal surfacefeature. For example, a perceivable feature may include a perceivableusual, regular, or typical surface feature. For example, perceivablefeature may include a perceivable abnormal surface feature. For example,a perceivable abnormal feature may include perceivable unusual,irregular, or disease state. For example, a perceivable abnormal featuremay include perceivable scar tissue, healed lesion, nodule, orencapsulated foreign object. For example, a perceivable feature mayinclude a perceivable feature of a surface that is machinedistinguishable from another surface feature. For example, a perceivablefeature may include a perceivable surface feature that is machinedifferentiable from another perceivable surface feature. For example, acomputing machine may be able to differentiate between first surfacefeature and second surface feature, but may not be able to distinguishor discern why they are not the same. For example, where the surface isa surface of an object, the perceivable feature may include a structuralelement, or a surface variation. For example, a surface color variationmay include a red rust spot on a blue car. For example a surface texturevariation may include a rust corrosion spot on an otherwise intactsurface.

In an embodiment, the perceivable feature includes a human-visionperceivable feature. For example, a human-vision perceivable feature mayinclude a feature that is visible to the naked eye or using naturalhuman vision, including corrective lenses. In an embodiment, theperceivable feature includes an augmented human-vision perceivablefeature, such as a feature visible to the naked eye as a result ofcomputer implemented enhancement, or computer augmented vision. In anembodiment, the perceivable feature includes a machine-visionperceivable feature.

Continuing with reference to FIG. 3, the system 220 includes a featurematching circuit 228. The feature matching circuit is configured todetermine a substantial correspondence between (x) an extractedperceivable feature included in a border region segment of a selecteddigital image of the plurality of digital images and (y) an extracted atleast one respective perceivable feature included in the each digitalimage of the plurality of digital images other than the selected digitalimage (i.e., the plurality digital images minus the selected digitalimage). For example, if the feature matching circuit determines asubstantial correspondence, it may be configured to output a “1”, and ifthe feature matching circuit does not determine a substantialcorrespondence, it may be configured to output a “0”. With reference toFIG. 5 for example, if the selected digital image is digital image210.1, the feature matching circuit would find a substantialcorrespondence between (x) the perceivable feature A included in aborder region segment of the digital image 210.1 and (y) the perceivablefeature A included in the digital image 210.4, and would thus output a“1”. The feature matching circuit would not find a substantialcorrespondence between (x) the perceivable feature A included in theborder region segment of the selected digital image 210.1 and (y) any ofthe other the perceivable features included in the digital images 210.2and 210.3, and would respectively output a “0” in response to at leastone respective perceivable feature included in each digital image of theplurality of digital images 210.2-210.3. For example, with reference toFIG. 5, the feature matching circuit would not find a substantialcorrespondence between (x) the perceivable feature C included in anotherborder region segment of the selected digital image 210.1 and (y) any ofthe other the perceivable features included in the digital images210.2-210.4, and would respectively output a “0” in response to at leastone respective perceivable feature included in each digital image of thedigital images 210.2-210.4.

Continuing with reference to FIG. 3, the system 220 also includes a datacollection circuit 232 configured to gather the determined substantialcorrespondences for the extracted perceivable feature included in theborder region segment of the selected digital image. With reference tothe example of FIG. 5 described above, in an embodiment, the datacollection circuit would gather the “1” and “0” outputted by the featurematching circuit 228. With reference to the perceivable feature Aincluded in a border region segment of the selected digital image 210.1,the gathered outputs would be a single “1” for the digital image 210.04and at least one “0” for digital images 210.2 and 210.3, i.e. [1,0,0].With reference to the perceivable feature C included in a border regionsegment of the selected digital image 210.1, the gathered outputs wouldbe all “0” for digital images 210.2-210.4, i.e. [0,0,0].

The system 220 also includes a reporting circuit 236. The reportingcircuit is configured to output informational data indicative of apossible non-imaged portion of the region of interest 202 of the surface201. For example, the informational data may be indicative of thepossible non-imaged portion 218 of the region of interest 202 of thesurface 201 illustrated in FIG. 6. The informational data is responsiveto an absence of a determined substantial correspondence between theextracted perceivable feature included in the border region segment ofthe selected digital image and the extracted at least one respectiveperceivable feature included in the each digital image of the pluralityof digital images other than the selected digital image. With referenceto the example of FIG. 5 described above, the data collection circuit232 would have gathered an absence of a determined substantialcorrespondence [0,0,0] between the perceivable feature C included in aborder region segment of the selected digital image 210.1 and at leastone respective perceivable feature included in each digital image of theplurality of digital images 210.2-210.4 other than the selected digitalimage. In an embodiment, the reporting circuit interprets an absence ofa determined substantial correspondence as indicia of a possiblenon-imaged portion of the region of interest adjacent to the selecteddigital image.

In an embodiment of the system, each digital image of the plurality ofdigital images includes an indication of a position or location relativeto the region of interest of the surface. In an embodiment, theplurality of digital images respectively includes a plurality of medicalimages of a portion of a region of interest of a surface of anindividual mammal. In an embodiment, each medical image of the pluralityof medical images respectively includes a portion of a region ofinterest of an internal surface of an individual mammalian body part. Inan embodiment, the plurality of medical images of an internal surface ofan individual mammalian body part was acquired by a body-insertabledevice. In an embodiment, the plurality of medical images of an internalsurface of an individual mammalian body part were acquired by an ex vivodevice. In an embodiment, each medical image of the plurality of medicalimages respectively includes a portion of a region of interest of anexternal surface of an individual mammal. In an embodiment, each digitalimage of the plurality of digital images respectively includes a portionof a region of interest of a surface of an object. For example, theobject may include the earth or planetary surface, a planetary body,ocean floor, a product, an aircraft, a machine, or a boat. In anembodiment, each digital image of the plurality of digital imagesincludes a respective identifier. For example, an identifier may includean alpha-numeric identifier. In an embodiment, the identifier may beused to identify a digital image adjacent to the possible non-imagedportion of the region of interest. In an embodiment, each digital imageof the plurality of digital images includes a respective identifierassigned by a receiver circuit operatively coupled to the system. In anembodiment, each digital image of the plurality of digital imagesincludes a respective identifier assigned by the system. In anembodiment, each digital image of the plurality of digital imagesincludes a respective identifier assigned by the system after receipt byan image receiver circuit. In an embodiment, each digital image of theplurality of digital images includes a respective identifier assigned byanother system.

In an embodiment, the feature matching circuit 228 includes a featurematching circuit configured to determine a substantial correspondencebetween (x) an extracted perceivable feature included in a border regionsegment of a selected digital image of the plurality of digital imagesand (y) an extracted at least one respective perceivable feature of aborder region segment of the each digital image of the plurality ofdigital images other than the selected digital image. For example, thismay be thought of as edge-feature to edge-feature correspondence ormatching. In this embodiment, the feature matching circuit is matchingwith respect to perceivable features in border region segments of bothimages. In an embodiment, the feature matching circuit includes afeature matching circuit configured to determine a substantialcorrespondence between (x) an extracted perceivable feature included ina border region segment of a selected digital image and (y) an extractedat least one respective perceivable feature of a field of view of eachdigital image of the plurality of digital images other than the selecteddigital image.

In an embodiment, the system 220 includes an image receiver circuitconfigured to receive the plurality of digital images. In an embodiment,the system includes a border region detection circuit 226 configured todetect a border region segment of a digital image. In an embodiment, theborder region detection circuit includes a border region detectioncircuit configured to select a length and/or a width parameter of theborder regions. The border region detection circuit is also configuredto detect a border region segment having the selected length and/orwidth. For example, the length and/or a width parameter of the borderregions may be a percentage of a dimension of the image, or may be aspecific length, or a specific number of pixels. For example, the lengthand/or a width parameter of the border regions may be dynamically varieddepending on a result of the feature matching, or depending on speed andprocessing horsepower available to the system. For example, the lengthand/or a width parameter of the border regions may be dynamically variedto provide an increased resolution in transition regions. In anembodiment, the border region detection circuit includes a border regiondetection circuit configured to receive a selected length and/or a widthparameter of the border regions. The border region detection circuit isalso configured to detect a border region segment of a digital imagehaving the selected length and/or width parameter. In an embodiment, thefeature-matching circuit 228 includes a feature-matching circuitconfigured to determine a substantial correspondence between (x) aperceivable feature included in the detected border region segment of aselected digital image of the plurality of digital images and (y) atleast one respective perceivable feature included in each digital imageof the plurality of digital images other than the selected digitalimage.

In an embodiment, the feature-matching circuit 228 includes afeature-matching circuit configured to (i) determine a substantialcorrespondence between (x) a perceivable feature included in a borderregion segment of a selected digital image of the plurality of digitalimages and (y) at least one respective perceivable feature included ineach digital image of the plurality of digital images other than theselected digital image. The feature-matching circuit is also configuredto (ii) iteratively designate a next perceivable feature included in anext border region segment of the selected digital image. The featurematching circuit is further configured to (iii) initiate a determinationof a substantial correspondence of the iteratively designated nextperceivable feature included in the next border region segment pursuantto element (i). With reference to FIG. 5 for example, this embodimentwill step through at least two iterations by looking for substantialcorrespondence for perceivable feature A and perceivable feature B. Inan embodiment, the data collection circuit 232 includes a datacollection circuit configured to gather the determined substantialcorrespondences for the respective perceivable feature included in therespective border region segments of the selected digital image. In anembodiment, the reporting circuit 236 includes a reporting circuitconfigured to output informational data indicative of a possiblenon-imaged portion of the region of interest of the surface. Theinformational data is responsive to an absence of a determinedsubstantial correspondences between the extracted respective perceivablefeature included in the respective border region segments of the atleast two border region segments of the selected digital image and theextracted at least one respective perceivable feature included in theeach digital image of the plurality of digital images other than theselected digital image.

In an embodiment, the system 220 includes an overlap-analysis circuit234 configured to generate data indicative of a border region-overlapstatus of the selected digital image. The data is generated at leastpartially in response to the determined substantial correspondencebetween the extracted perceivable feature included in the border regionsegment of the selected digital image and the extracted at least onerespective perceivable feature included in the each digital image of theplurality of digital images other than the selected digital image. Forexample, a determined absence of a substantial correspondence forperceivable feature in one border region segment of the selected digitalimage may result in generation of data indicative on a “border regionnot overlapped” status. With reference to the example of FIG. 5described above, and in reference to the perceivable feature C includedin a border region segment of the selected digital image 210.1; wherethe gathered determined substantial correspondences for perceivablefeature C are all “0” (i.e. [0,0,0]), the overlap-analysis circuitgenerates data indicative of a “border region not overlapped” status forthe border region segment of the digital image 210.1 that includesperceivable feature C. For example, a determined a substantialcorrespondence for a perceivable feature in one detected border regionsegment of the selected digital image may result in generation of dataindicative of a “border region overlapped” status. With reference to theexample of FIG. 5 described above, and in reference to the perceivablefeature A included in a border region segment of the selected digitalimage 210.1; where the gathered determined substantial correspondencesfor the perceivable feature A include a “1” with respect to digitalimage 210.4, the overlap-analysis circuit generates data indicative of a“border region overlapped” status for the border region segment of thedigital image 210.1 that includes perceivable feature A. In anembodiment, the reporting circuit 236 includes a reporting circuitconfigured to output informational data indicative of the borderregion-overlap status of the selected digital image. The informationaldata is at least partially based on the data indicative of a borderregion-overlap status of the selected digital image.

In an embodiment, the overlap-analysis circuit 234 includes anoverlap-analysis circuit configured to generate data indicative of apossible non-imaged portion of the region of interest adjacent to theselected digital image. In an embodiment, the reporting circuit 236includes a reporting circuit configured to output informational dataindicative of the possible non-imaged portion of the region of interestadjacent to the selected digital image. The informational data is atleast partially based on the data indicative of the possible non-imagedportion of the region of interest adjacent to the selected digitalimage. In an embodiment, the overlap-analysis circuit includes anoverlap-analysis circuit configured to generate data indicative of apossible non-imaged portion of the region of interest adjacent to boththe selected digital image and another selected digital image. In anembodiment, the overlap-analysis circuit includes an overlap-analysiscircuit configured to generate data indicative of a predicted possiblenon-imaged portion of the region of interest adjacent to the selecteddigital image. In an embodiment, the prediction may be based onfiltering or applying a prediction algorithm.

Continuing with FIG. 3, in an embodiment, the overlap-analysis circuit234 includes an overlap-analysis circuit configured to generate dataindicative of a possible imaged portion of the region of interestadjacent to the selected digital image. In an embodiment, theoverlap-analysis circuit 234 includes an overlap-analysis circuitconfigured to generate data indicative of a possible non-imaged portionof the region of interest adjacent to the selected digital image andindicative of a spatial relationship between the possible non-imagedportion of the region of interest and the feature. In an embodiment, thespatial relationship may be indicated with respect to a site, center, orquadrant of the border region segment of the selected digital image.FIG. 6 provides a partial illustration of this embodiment. Theembodiment provides data indicative of a spatial relationship 216between the possible non-imaged portion 218 of the region of interest202 and the perceivable feature included in the border region segment(although FIG. 6 illustrates a situation where the perceivable feature Wis not included in the border region). In an embodiment, theoverlap-analysis circuit 234 includes an overlap-analysis circuitconfigured to generate data indicative of a possible non-imaged portionof the region of interest adjacent to the selected digital image; andindicative of a spatial relationship between the possible non-imagedportion of the region of interest and the feature included in a borderregion segment of the selected digital image. The spatial relationshipis indicated by a line anchored by a feature, site, center, or quadrantof the selected digital image. FIG. 6 provides an illustration of thisembodiment. The data of this embodiment provides an indication of thespatial relationship 216 between the possible non-imaged portion 218that is anchored by the perceivable feature W. In an embodiment, thedetermined spatial relationship is indicated by a line anchored by afeature, site, center, or quadrant of the selected digital image andsubstantially perpendicular to an edge of the field of view of thedigital image.

In an embodiment, the overlap-analysis circuit 234 includes anoverlap-analysis circuit configured to generate data indicative of apossible non-imaged portion of the region of interest adjacent to theselected digital image and indicative of a spatial relationship betweenthe possible non-imaged portion of the region of interest and ahuman-perceivable feature included in the border region segment of theselected digital image. The determined spatial relationship indicated bya line anchored by a feature, site, center, or quadrant of the selecteddigital image.

In an embodiment, the reporting circuit 236 includes a reporting circuitconfigured to output informational data indicative of a possiblenon-imaged portion of the region of interest adjacent to the selecteddigital image of the surface. For example, the informational data mayinclude an identification number assigned to the selected digital image,or location information associated with the selected digital image. Inan embodiment, the reporting circuit includes a reporting circuitconfigured to output informational data indicative of a possiblenon-imaged portion of the region of interest of the surface. Theinformational data is responsive to (i) an absence of a determinedsubstantial correspondence between the extracted perceivable featureincluded in the border region segment of the selected digital image anda first extracted perceivable feature included in a first digital imageof the plurality of digital images other than the selected digitalimage, and to (ii) an absence of a determined substantial correspondencebetween the extracted perceivable feature included in the border regionsegment of the selected digital image and a second extracted perceivablefeature included in a second digital image of the plurality of digitalimages other than the selected digital image.

In an embodiment, the system 220 includes computer-readable media 239configured to maintain the informational data. In an embodiment, thecomputer-readable media may be managed by a computer storage device 238.In an embodiment, the computer-readable media may include acomputer-readable media configured to maintain and to provide access tothe informational data. In an embodiment, the computer-readable mediamay include a tangible computer-readable media. In an embodiment, thecomputer-readable media may include a communications media. In anembodiment, the system includes a communication device configured toprovide a notification at least partially based on the informationaldata to at least one of a human, computer, or system. For example, thecommunications device may be incorporated into the system, asillustrated by the communication device 242. In another example, thecommunication device may be a third-party device in communication withthe system as illustrated by the computing device 292 having the screen294. In an embodiment, the communication device is configured to displaya human-perceivable depiction of the informational data. In anembodiment, the communication device is configured to output a signalusable in displaying a human-perceivable depiction of the informationaldata. For example, the human-perceivable depiction may include a visualor an audio human-perceivable depiction of the informational data.

In an embodiment, the system 220 includes a processor 250. In anembodiment, the processor may be at least substantially similar to theprocessing unit 21 described in conjunction with FIG. 1. In anembodiment, the processor may be at least substantially similar to theprocessor 120 described in conjunction with FIG. 2.

FIG. 3 also illustrates an alternative embodiment of a system 200. Thealternative embodiment of the system includes the feature-matchingcircuit 228 configured to determine a substantial correspondence between(x) a perceivable feature included in a border region segment of aselected digital image of a plurality of digital images and (y) at leastone respective perceivable feature included in each digital image of theplurality of digital images other than the selected digital image, theeach digital image of the plurality of digital images includes arespective portion of a region of interest of a surface. The datacollection circuit 232 is configured to gather the determinedsubstantial correspondences for the perceivable feature included in theborder region segment of the selected digital image. The reportingcircuit 236 is configured to output informational data indicative of apossible non-imaged portion of the region of interest of the surface.The informational data is responsive to an absence of a determinedsubstantial correspondence in the gathered determined substantialcorrespondences. In an embodiment, the reporting circuit is configuredto output informational data indicative of a possible non-imaged portionof the region of interest of the surface. The informational data isresponsive to an absence of any determined substantial correspondencesin the gathered determined substantial correspondences.

FIG. 7 illustrates an example operational flow 300 implemented in acomputing device. After a start operation, the operational flow includesa detection operation 330. The detection operation includes extractingat least one respective perceivable feature included in each digitalimage of a plurality of digital images. The each digital image of theplurality of digital images includes a respective portion of a region ofinterest of a surface. In an embodiment, the detection operation may beimplemented using the feature-detection circuit 224 described inconjunction with FIG. 3. A feature correspondence operation 340 includesdetermining a substantial correspondence between (x) an extractedperceivable feature included in a border region segment of a selecteddigital image of the plurality of digital images and (y) an extracted atleast one respective perceivable feature included in each digital imageof the plurality of digital images other than the selected digitalimage. In an embodiment, the feature correspondence operation may beimplemented using the feature matching circuit 228 described inconjunction with FIG. 3. A data collection operation 350 includesgathering the determined substantial correspondences for the extractedperceivable feature included in the border region segment of theselected digital image. In an embodiment, the data collection operationmay be implemented using the data collection circuit 232 described inconjunction with FIG. 3. A reporting operation 370 includes outputtinginformational data indicative of a possible non-imaged portion of theregion of interest of the surface. The informational data is responsiveto an absence of a determined substantial correspondence between theextracted perceivable feature included in the border region segment ofthe selected digital image and the extracted at least one respectiveperceivable feature included in the each digital image of the pluralityof digital images other than the selected digital image. In anembodiment, the reporting operation may be implemented using thereporting circuit 236 described in conjunction with FIG. 3. Theoperational flow includes an end operation.

FIG. 8 illustrates an alternative embodiment of the example operationalflow 300 of FIG. 7. The alternative embodiment may include at least oneadditional operation. An additional operation may include an operation310, an operation 320, or an operation 380. The operation 310 includesreceiving the plurality of digital images. The operation 320 includesdetecting a border region segment of the selected digital image. In anembodiment, the operation 320 may include at least one additionaloperation, such as an operation 322 or an operation 324. The operation322 includes selecting a length and/or a width parameter of the borderregion, and detecting the border region segment of the selected digitalimage having the selected length and/or width parameter. The operation324 includes receiving a selected length and/or a width parameter of theborder region, and detecting the border region segment of the selecteddigital image having the selected length and/or width parameter. Theoperation 380 may include at least one additional operation, such as anoperation 382, an operation 384, an operation 386, or an operation 388.The operation 382 includes iteratively designating a next digital imagefrom the plurality of digital images as the selected digital image untileach digital image of the plurality of digital images has beendesignated. The operation 382 includes initiating a processing of eachof the iteratively designated next digital images. The processingincludes operations 330, 340 and 350. The operation 384 includesdisplaying the informational data. The operation 386 includesmaintaining the informational data in computer-readable storage media.The operation 388 includes providing a notification at least partiallybased on the informational data to at least one of a human, computer, orsystem.

FIG. 9 illustrates an alternative embodiment of the example operationalflow 300 of FIG. 7. The operational flow may include an overlap-analysisoperation 360. The overlap-analysis operation includes generating dataindicative of a border region-overlap status of the selected digitalimage. The data is generated at least partially in response to thedetermined substantial correspondences between the extracted perceivablefeature included in the border region segment of the selected digitalimage and the extracted at least one respective perceivable featureincluded in the each digital image of the plurality of digital imagesother than the selected digital image. The overlap-analysis operation360 may include at least one additional operation, such as the operation364. The operation 364 includes generating data indicative of a possiblenon-imaged portion of the region of interest adjacent to the selecteddigital image. The data is generated at least partially in response tothe determined substantial correspondences between the extractedperceivable feature included in the border region segment of theselected digital image and the extracted at least one respectiveperceivable feature included in the each digital image of the pluralityof digital images other than the selected digital image. The reportingoperation 370 may include at least one additional operation. The atleast one additional operation may include an operation 372, anoperation 374, an operation 376, or an operation 378. The operation 372includes outputting informational data indicative of a possiblenon-imaged portion of the region of interest of the surface. Theinformational data is at least partially based on the data indicative ofa border region-overlap status of the selected digital image. Theoperation 374 includes outputting informational data indicative of thepossible non-imaged portion of the region of interest adjacent to theselected digital image. The informational data is at least partiallybased on the data indicative of the possible non-imaged portion of theregion of interest adjacent to the selected digital image. The operation376 includes outputting informational data usable in displaying ahuman-perceivable indication of the possible non-imaged portion of theregion of interest of the surface. The operation 378 includes outputtinginformational data configured to provide a particular visual depictionof a possible non-imaged portion of the region of interest of thesurface.

FIG. 7 illustrates an alternative embodiment of the operational flow 300implemented in a computing device. After a start operation, theoperational flow includes a feature correspondence operation 340. Thefeature correspondence operation includes determining a substantialcorrespondence between (x) a perceivable feature included in a borderregion segment of a selected digital image of a plurality of digitalimages and (y) at least one respective perceivable feature included ineach digital image of the plurality of digital images other than theselected digital image, the each digital image of the plurality ofdigital images includes a respective portion of a region of interest ofa surface. In an embodiment, the feature correspondence operation may beimplemented using the feature matching circuit 228 described inconjunction with FIG. 3. A data collection operation 350 includesgathering the determined substantial correspondences for the perceivablefeature included in the border region segment of the selected digitalimage. In an embodiment, the data collection operation may beimplemented using the data collection circuit 232 described inconjunction with FIG. 3. A reporting operation 370 includes outputtinginformational data indicative of a possible non-imaged portion of theregion of interest of the surface, the informational data responsive toan absence of a determined substantial correspondence in the gathereddetermined substantial correspondences. In an embodiment, the reportingoperation may be implemented using the reporting circuit 236 describedin conjunction with FIG. 3. The operational flow includes an endoperation.

FIG. 10 illustrates an example computer program product 400. Thecomputer program product includes computer-readable media 410 bearingprogram instructions 420. The program instruction, when executed by aprocessor of a computing device, cause the computing device to perform aprocess. The process includes (a) extracting at least one respectiveperceivable feature included in each digital image of a plurality ofdigital images. The each digital image of the plurality of digitalimages includes a respective portion of a region of interest of asurface. The process also includes (b) determining a substantialcorrespondence between (x) an extracted perceivable feature included ina border region segment of a selected digital image of the plurality ofdigital images and (y) an extracted at least one respective perceivablefeature included in each digital image of the plurality of digitalimages other than the selected digital image. The process also includes(c) gathering the determined substantial correspondences for theextracted perceivable feature included in the border region segment ofthe selected digital image. The process also includes (d) outputtinginformational data indicative of a possible non-imaged portion of theregion of interest of the surface. The informational data is responsiveto an absence of a determined substantial correspondence between theextracted perceivable feature included in the border region segment ofthe selected digital image and the extracted at least one respectiveperceivable feature included in each digital image of the plurality ofdigital images other than the selected digital image.

In an alternative embodiment, the process (d) outputting informationaldata includes 422 transforming the informational data into a particularvisual depiction of a possible non-imaged portion of the region ofinterest of the surface, and outputting the transformed informationaldata. In an embodiment, the process may include 424 (e) providing anotification at least partially based on the informational data to atleast one of a human, computer, or system. In an embodiment, thecomputer-readable media includes a tangible computer-readable media 412.In an embodiment, the computer-readable media includes a communicationsmedia 414.

FIG. 11 illustrates an example system 500. The system includes means 510for extracting at least one respective perceivable feature included ineach digital image of a plurality of digital images. The each digitalimage of the plurality of digital images includes a respective portionof a region of interest of a surface. The system includes means 520 fordetermining a substantial correspondence between (x) an extractedperceivable feature included in a border region segment of a selecteddigital image of the plurality of digital images and (y) an extracted atleast one respective perceivable feature included in each digital imageof the plurality of digital images other than the selected digitalimage. The system includes means 530 for gathering the determinedsubstantial correspondences for the extracted perceivable featureincluded in the border region segment of the selected digital image. Thesystem includes means 540 for outputting informational data indicativeof a possible non-imaged portion of the region of interest of thesurface. The informational data responsive to an absence of a determinedsubstantial correspondence between the extracted perceivable featureincluded in the border region segment of the selected digital image andthe extracted at least one respective perceivable feature included inthe each digital image of the plurality of digital images other than theselected digital image.

In an alternative embodiment, the system may include means 550 fordetecting a border region segment of the selected digital image. In analternative embodiment, the system may include means 560 for generatingdata indicative of a border region-overlap status of the selecteddigital image. The data is generated at least partially in response tothe determined substantial correspondence between the extractedperceivable feature included in the border region segment of theselected digital image and the extracted at least one respectiveperceivable feature included in the each digital image of the pluralityof digital images other than the selected digital image. In analternative embodiment, the system may include means 570 for displayingthe informational data.

FIG. 12 illustrates an example environment 600. The environment includesthe surface 201, the digital image acquisition device 205, the pluralityof digital images 210, a system 620, and the computing device 292 havingthe screen 294 visible to the person 296.

The system 620 includes a feature-detection circuit 624 configured toextract at least one respective perceivable feature included in eachdigital image of a plurality of digital images 210. The each digitalimage of the plurality of digital images includes a respective portionof the region of interest 202 of the surface 201. The system includes afeature-matching circuit 628 configured to determine a substantialcorrespondence between (x) an extracted perceivable feature included ina border region segment of a selected digital image of the plurality ofdigital images and (y) an extracted at least one respective perceivablefeature included in each digital image of the plurality of digitalimages other than the selected digital image. The system includes a datacollection circuit 632 configured to gather the determined substantialcorrespondences for the extracted perceivable feature included in theborder region segment of the selected digital image. The system includesan overlap-analysis circuit 634 configured to generate data indicativeof a border region-overlap status of the selected digital image. Thedata is generated at least partially in response to the gathereddetermined substantial correspondences. The system includes a listmanagement circuit 644 configured to add the data indicative of thedetermined border region-overlap status for the border region segment ofthe selected digital image to an omitted-coverage list. For example, inan embodiment, the determined border region-overlap status may include“likely not overlapped,” or “likely overlapped.”

The system 620 includes 646 an iteration control circuit configured toiteratively designate a next digital image from the plurality of digitalimages as the selected digital image until each digital image of theplurality of digital images has been designated. The iteration controlcircuit is also configured to initiate a processing of each of theiteratively designated next digital images by the feature-matchingcircuit 628, the data collection circuit 632, the overlap-analysiscircuit 634, and the list management circuit 644. In an alternativeembodiment, the iteration circuit is also configured to initiate aprocessing of each of the iteratively designated next digital images bya border region detection circuit 626. The system includes acoverage-analysis circuit 648 configured to identify a particularportion of the region of interest of a surface as likely not included inthe plurality of digital images (hereafter “possible non-imaged portionof the region of interest”). The identification of the possiblenon-imaged portion of the region of interest is at least partially basedon the omitted-coverage list. In an embodiment, the coverage-analysiscircuit is configured to at least one of determine, classify, find, orlocate a possible non-imaged portion of the region of interest. Thesystem includes a reporting circuit 636 configured to outputinformational data indicative of the possible non-imaged portion of theregion of interest. In an embodiment, the informational data includes anindication that the possible non-imaged portion of the region ofinterest may be adjacent to a particular digital image of the pluralityof digital images.

In an alternative embodiment, the system 620 includes an image receivercircuit 622 configured to receive a plurality of digital images. In analternative embodiment, the system includes a border region detectioncircuit 626 configured to detect a border region segment of a digitalimage of the plurality of digital images. In an alternative embodiment,the feature matching circuit 628 includes a feature-matching circuitconfigured to determine a substantial correspondence between (x) anextracted perceivable feature included in a detected border regionsegment of a selected digital image of the plurality of digital imagesand (y) an extracted at least one respective perceivable featureincluded in each digital image of the plurality of digital images otherthan the selected digital image.

In an alternative embodiment, the data collection circuit 632 includes adata collection circuit configured to gather and assemble the determinedsubstantial correspondences for the extracted perceivable featureincluded in the border region segment of the selected digital image. Inan alternative embodiment, the data collection circuit includes a datacollection circuit configured to gather the determined substantialcorrespondences for a respective perceivable feature included in eachrespective border region segment of the selected digital image.

In an alternative embodiment, the coverage-analysis circuit 648 includesa coverage-analysis circuit configured to identify a particular portionof the region of interest of a surface as likely not included in theplurality of digital images (hereafter “possible non-imaged portion ofthe region of interest”) and to identify at least one digital image ofthe plurality of digital images (hereafter “signpost digital image”) asspatially proximate to the possible non-imaged portion of the region ofinterest. The identification of the possible non-imaged portion of theregion of interest and the identification of the signpost digital imageis at least partially based on the omitted-coverage list. With referenceto the example of FIG. 6 described above, the coverage-analysis circuitmay identify for example at least one of images 210.3, 210.5, 210.6, and210.7 as the signpost digital image spatially proximate to the possiblenon-imaged portion of the region of interest 218. In an alternativeembodiment, for example, if the digital image 210.8 included a readilyperceivable feature such as a mole, the coverage-analysis circuit mayidentify the digital image 210.8 as the signpost digital image adjacentto the possible non-imaged portion of the region of interest 218 eventhough the digital image 210.8 is not immediately adjacent. Continuingwith FIG. 12, in an alternative embodiment, reporting circuit 636includes a reporting circuit configured to output informational dataindicative of the possible non-imaged portion of the region of interestadjacent to the selected digital image and of the signpost digitalimage.

In an alternative embodiment, the coverage-analysis circuit 648 includesa coverage-analysis circuit configured to identify a particular portionof the region of interest of a surface as likely not included in theplurality of digital images (hereafter “possible non-imaged portion ofthe region of interest”). The identification of the possible non-imagedportion of the region of interest is at least partially based onapplication of a filter or a template to the omitted-coverage list. Forexample, the filter may include a threshold requirement that a certainminimum number of adjacent border region segments of the selecteddigital image have a “likely not overlapped” determined borderregion-overlap status before identification of a particular portion ofthe region of interest of a surface as likely not included in theplurality of digital images.

FIG. 13 partially illustrates an application of an alternativeembodiment of the coverage-analysis circuit 648 to the plurality ofdigital images 210 previously illustrated in FIG. 6. In the alternativeembodiment, the coverage-analysis circuit 648 includes acoverage-analysis circuit configured to (i) identify a particularportion 218 of the region of interest 202 of a surface 201 as likely notincluded in the plurality of digital images (hereafter “possiblenon-imaged portion of the region of interest”). The identification ofthe possible non-imaged portion of the region of interest is at leastpartially based on the omitted-coverage list. The coverage-analysiscircuit is also configured to (ii) identify at least three digitalimages of the plurality of digital images immediately adjacent to thepossible non-imaged portion of the region of interest. Theidentification of the at least three digital images is at leastpartially based on the omitted-coverage list. In a first example, afirst set of identified at least three digital images includes digitalimages 210.3, 210.5, 210.6, and 210.7. The coverage-analysis circuit isalso configured to (iii) define a simple closed curve formed by linkingat least one detected border region segment of each of the at leastthree identified digital images, wherein the border region segments eachhave an overlap status of “likely not overlapped”. For example, a simpleclosed curve, sometimes known as a Jordan curve, includes a non-selfintersecting closed curve, i.e., a connected curve that does not crossitself and ends at the same point where it begins. A first simple closedcurve 652 is formed by linking at least one detected border regionsegment of each of the at least three identified digital images, whereinthe border region segments each have an overlap status of “likely notoverlapped.” The coverage-analysis circuit is also configured to (iv)determine whether the possible non-imaged portion of the region ofinterest lies substantially inside or substantially outside of theregion of interest. The determination is at least partially based on thepositions of the identified at least three digital images relative tothe closed curve. FIG. 13 illustrates the positions of the first set ofthe identified at least three digital images (210.3, 210.5, 210.6, and210.7) as substantially outside of the first closed curve 652. As aresult, the coverage-analysis circuit would determine that the firstpossible non-imaged portion 218 of the surface lies inside of the regionof interest. In a second example, a second possible non-imaged portion219 of the surface is identified. A second set of identified at leastthree digital images includes digital images 210.1, 210.2, and 210.4. Asecond simple closed curve 654 is formed by linking at least onedetected border region segment of each of the second set of at leastthree identified digital images, wherein the border region segments eachhave an overlap status of “likely not overlapped.” FIG. 13 illustratesthe positions of the second set of identified at least three digitalimages (210.1, 210.2, and 210.4) as substantially inside the secondclosed curve 654. As a result, the coverage-analysis circuit woulddetermine that the second possible non-imaged portion 219 of the surfacelies outside of the region of interest. Continuing with reference toFIG. 12, in an embodiment, the reporting circuit 636 includes areporting circuit configured to output informational data indicative ofthe identified possible non-imaged portion of the region of interest andindicative of the determination whether the possible non-imaged portionof the region of interest lies inside or outside of the region ofinterest.

FIG. 13 partially illustrates another alternative embodiment of thecoverage-analysis circuit 648. In an alternative embodiment, thecoverage-analysis circuit includes a coverage-analysis circuitconfigured to (i) tentatively identify a particular portion of theregion of interest 202 of the surface 201 as likely not included in theplurality of digital images 210 (hereafter “tentative non-imagedportion”). The “tentative non-imaged portion” is identified at leastpartially based on an analysis of the omitted-coverage list. Thecoverage-analysis circuit is also configured to (ii) determine if the“tentative non-imaged portion” likely includes an outer peripheryportion of the region of interest included in the plurality of digitalimages. For example, a first “tentative non-imaged portion” of thisalternative embodiment may be illustrated by the first non-imagedportion 218 and a second “tentative non-imaged portion” of thisalternative embodiment may be illustrated by the second non-imagedportion 219. Any technique known to those of skill in the art may beused to make this determination. For example, the coverage-analysiscircuit may use the previously described technique of defining a simpleclosed curve linking at least one border region segment of each of atleast three identified digital images adjacent to a “tentativenon-imaged portion of the region of interest” and determining whetherthe “tentative non-imaged portion of the region of interest” lies insideor outside of the region of interest. As described above, the first“tentative non-imaged portion” of this alternative embodiment by thefirst non-imaged portion 218 would be determined as “likely does notinclude an outer periphery of the region of interest included in theplurality of digital images.” Also as described above, the second“tentative non-imaged portion” of this alternative embodimentillustrated by the second non-imaged portion 219 would be determined a“likely does include an outer periphery of the region of interestincluded in the plurality of digital images.”

In this embodiment, the coverage-analysis circuit 648 is also configured(iii) if the identified “tentative non-imaged portion” likely does notinclude an outer periphery of the region of interest 202 included in theplurality of digital images 210, to classify the “tentative non-imagedportion” as a “possible non-imaged portion of the region of interest.”Continuing with the above example, since the first “tentative non-imagedportion,” illustrated by the first possible non-imaged portion 218,would be determined as likely does not include an outer periphery of theregion of interest included in the plurality of digital images, thecoverage-analysis circuit will classify it as a “possible non-imagedportion of the region of interest.” The reporting circuit 636 willoutput informational data indicative of the possible non-imaged portion218 of the region of interest. Continuing with the above example, sincethe second “tentative non-imaged portion,” illustrated by the secondpossible non-imaged portion 219, would be determined as likely doesinclude an outer periphery of the region of interest included in theplurality of digital images, the coverage-analysis circuit will notclassify it as a “possible non-imaged portion of the region ofinterest.” As a result, the reporting circuit will not outputinformational data indicative of the possible non-imaged portion of theregion of interest 219. An advantage of this embodiment is that thereporting circuit will not output informational data indicative of“possible non-imaged portions of the region of interest” lying on theouter periphery of the plurality of digital images. Since the pluralityof digital images only describe a part of the surface 201, theseunbounded regions may be beyond the desired region of interest of thesurface and are in effect winnowed out of the reporting.

Continuing with reference to FIG. 12, in an embodiment, the reportingcircuit 636 includes a reporting circuit configured to output arendering of the informational data in a form facilitating ahuman-perceivable representation of the informational data. For example,the reporting circuit may be configured to output a rendering of theinformational data optimized in a form facilitating a human-perceivablerepresentation of the informational data on a portable display, such asa display device associated with the communication device 642, or thescreen 294 associated with the computing device 292. For example, thereporting circuit may be configured to output the informational data ina format facilitating a human-viewable representation of theinformational data.

In an embodiment, the feature-detection 624 circuit includes afeature-detection circuit configured to extract at least one surfacefeature included in a digital image of the plurality of digital images210. In an embodiment, the feature-detection circuit includes afeature-detection circuit configured to extract at least one surfacefeature included in a border region segment of a digital image of theplurality of digital images. See the border region segment 211.1 of FIG.4 for an example of a surface feature included in a border regionsegment. In an embodiment, the feature-detection circuit includes afeature-detection circuit configured to extract at least onehuman-perceivable feature included in a digital image of the pluralityof digital images. In an embodiment, the feature-detection circuitincludes a feature-detection circuit configured to extract at least onehuman vision perceivable feature included in a digital image of theplurality of digital images. In an embodiment, the feature-detectioncircuit includes a feature-detection circuit configured to extract atleast one feature included in a border region segment of a digital imageof the plurality of digital images. In an embodiment, thefeature-detection circuit includes a feature-detection circuitconfigured to extract at least one feature included in the field of viewof a digital image of the plurality of digital images. In an embodiment,the feature-detection circuit includes a feature-detection circuitconfigured to detect and extract at least one feature included in adigital image of the plurality of digital images. In an embodiment, thefeature-detection circuit includes a feature-detection circuitconfigured to detect and extract a human-perceivable feature included ina digital image of the plurality of digital images.

In an embodiment, the iteration control circuit 646 includes aniteration control circuit configured to iteratively designate a nextdigital image from the plurality of digital images 210 as the selecteddigital image (hereafter “iteratively designed selected digital image”)until each digital image of the plurality of digital images has beendesignated. The iteration control circuit is configured to initiate ageneration of data indicative of a border region-overlap status for eachiteratively designated selected digital image. The iteration controlcircuit is configured to add the data indicative of a determined borderregion-overlap status for each iteratively designated selected digitalimage to the omitted-coverage list. In an embodiment, the system 620further includes computer-readable media 239 configured to maintain theinformational data.

FIG. 12 illustrates an alternative embodiment of the system 620. In thealternative embodiment, the system includes the feature-matching circuit628 configured to determine a substantial correspondence between (x) aperceivable feature included in a border region segment of a selecteddigital image of a plurality of digital images and (y) at least onerespective perceivable feature included in each digital image of theplurality of digital images other than the selected digital image. Theeach digital image of the plurality of digital images includes arespective portion of a region of interest of a surface. The alternativeembodiment of the system includes the data collection circuit 632configured to gather the determined substantial correspondences for theperceivable feature included in the border region segment of theselected digital image. The alternative embodiment of the systemincludes the overlap-analysis circuit 634 configured to generate dataindicative of a border region-overlap status of the selected digitalimage. The data is generated at least partially in response to thegathered determined substantial correspondences for the perceivablefeature. The alternative embodiment of the system includes the listmanagement circuit 644 configured to add the data indicative of thedetermined border region-overlap status to an omitted-coverage list. Thealternative embodiment of the system includes the iteration controlcircuit 646 configured to iteratively designate a next digital imagefrom the plurality of digital images as the selected digital image untileach digital image of the plurality of digital images has beendesignated. The iteration control circuit is also configured to initiatea processing of each of the iteratively designated next digital imagesby the feature-matching circuit, the data collection circuit, theoverlap circuit, and the list management circuit. The alternativeembodiment of the system includes the coverage-analysis circuit 648configured to identify a particular portion of the region of interest aslikely not included in the plurality of digital images (hereafter“possible non-imaged portion of the region of interest”). Theidentifying the possible non-imaged portion of the region of interest isat least partially based on the omitted-coverage list. The alternativeembodiment of the system includes the reporting circuit 636 configuredto output informational data indicative of the possible non-imagedportion of the region of interest.

FIG. 14 illustrates an example operational flow 700 implemented in acomputing device. After a start operation, the operational flow includesa detection operation 730. The detection operation includes extractingat least one respective perceivable feature included in each digitalimage of a plurality of digital images. The each digital image of theplurality of digital images includes a respective portion of a region ofinterest of a surface. In an embodiment, the detection operation may beimplemented using the feature-detection circuit 624 described inconjunction with FIG. 12. A feature correspondence operation 740includes determining a substantial correspondence between (x) anextracted perceivable feature included in a border region segment of aselected digital image of the plurality of digital images and (y) anextracted at least one respective perceivable feature included in eachdigital image of the plurality of digital images other than the selecteddigital image. In an embodiment, the feature correspondence operationmay be implemented using the feature-matching circuit 628 described inconjunction with FIG. 12. A data collection operation 750 includesgathering the determined substantial correspondences for the extractedperceivable feature included in the border region segment of theselected digital image. In an embodiment, the data collection operationmay be implemented using the data collection circuit 632 described inconjunction with FIG. 12. An overlap-analysis operation 760 includesgenerating data indicative of a border region-overlap status of theselected digital image. The data is generated at least partially inresponse to the gathered determined substantial correspondences. In anembodiment, the overlap-analysis operation may be implemented using theoverlap-analysis circuit 634 described in conjunction with FIG. 12. Alist management operation 765 includes adding the data indicative of thedetermined border region-overlap status for the border region segment ofthe selected digital image to an omitted-coverage list. In anembodiment, the list management operation may be implemented using thelist management circuit 644 described in conjunction with FIG. 12. Anext-image selection operation 770 includes iteratively designating anext digital image from the plurality of digital images as the selecteddigital image until each digital image of the plurality of digitalimages has been designated. In an embodiment, the next-image selectionoperation may be implemented using the iteration control circuit 646described in conjunction with FIG. 12. An iteration operation 775includes initiating a processing of each of the iteratively designatednext digital images, the processing includes operations 740, 750, 760,and 765. In an embodiment, the iteration operation may also beimplemented using the iteration control circuit 646 described inconjunction with FIG. 12. A coverage-analysis operation 780 includesidentifying a particular portion of the region of interest as likely notincluded in the plurality of digital images (hereafter “possiblenon-imaged portion of the region of interest”). The identification ofthe possible non-imaged portion of the region of interest is at leastpartially based on the omitted-coverage list. In an embodiment, thecoverage-analysis operation may be implemented using thecoverage-analysis circuit 648 described in conjunction with FIG. 12. Areporting operation 790 includes outputting informational dataindicative of the possible non-imaged portion of the region of interest.In an embodiment, the reporting operation may be implemented using thereporting circuit 636 described in conjunction with FIG. 12. Theoperational flow includes an end operation.

FIG. 15 illustrates an alternative embodiment of the example of theoperational flow 700 of FIG. 14. In an embodiment, the operational flowincludes an operation 710 receiving the plurality of digital images. Inan embodiment, the operational flow includes an operation 720 detectinga border region segment of the selected digital image.

FIG. 16 illustrates an alternative embodiment of the example of theoperational flow 700 of FIG. 14. In an embodiment, the reportingoperation 790 may include at least one additional operation. The atleast one additional operation may include an operation 792 or anoperation 794. The operation 792 includes outputting informational datausable in displaying a human-perceivable indication of the possiblenon-imaged portion of the region of interest. The operation 794 includesoutputting informational data configured to provide a particular visualdepiction of the possible non-imaged portion of the region of interest.In an embodiment, the operational flow 700 may include at least oneadditional operation 795. The at least one additional operation mayinclude an operation 796, an operation 797, or an operation 798. Theoperation 796 includes displaying the informational data. The operation797 includes maintaining the informational data in computer-readablestorage media. The operation 798 includes providing a notification atleast partially based on the informational data to at least one of ahuman, computer, or system.

FIG. 17 illustrates an example computer program product 800. Thecomputer program product includes computer-readable media 810 bearingprogram instructions 820. The program instructions, when executed by aprocessor of a computing device, cause the computing device to perform aprocess. The process includes (a) extracting at least one respectiveperceivable feature included in each digital image of a plurality ofdigital images. The each digital image of the plurality of digitalimages includes a respective portion of a region of interest of asurface. The process includes (b) determining a substantialcorrespondence between (x) an extracted perceivable feature included ina border region segment of a selected digital image of the plurality ofdigital images and (y) an extracted at least one respective perceivablefeature included in the each digital image of the plurality of digitalimages other than the selected digital image. The process includes (c)gathering the determined substantial correspondences for the extractedperceivable feature included in the border region segment of theselected digital image. The process includes (d) generating dataindicative of a border region-overlap status of the selected digitalimage. The data is generated at least partially in response to thegathered determined substantial correspondences. The process includes(e) adding the data indicative of the determined border region-overlapstatus for the border region segment of the selected digital image to anomitted-coverage list. The process includes (f) iteratively designatinga next digital image from the plurality of digital images as theselected digital image until each digital image of the plurality ofdigital images has been designated. The process includes (g) processingof each of the iteratively designated next digital images, theprocessing includes operations (b), (c), (d), and (e). The processincludes (h) identifying a particular portion of the region of interestas likely not included in the plurality of digital images (hereafter“possible non-imaged portion of the region of interest”). Theidentifying the possible non-imaged portion of the region of interest isat least partially based on the omitted-coverage list. The processincludes (i) outputting informational data indicative of the possiblenon-imaged portion of the region of interest.

In an embodiment, the (i) outputting informational data includes 822 (i)transforming the informational data into a particular visual depictionof a possible non-imaged portion of the region of interest andoutputting the transformed informational data. In an embodiment, theprocess further includes 824 (j) outputting informational data includesproviding a notification at least partially based on the informationaldata to at least one of a human, computer, or system. In an embodiment,the computer-readable media 810 includes a tangible computer-readablemedia 812. In an embodiment, the computer-readable media includes acommunications media 814.

FIG. 18 illustrates an example system 900. The system includes means 910for extracting at least one respective perceivable feature included ineach digital image of a plurality of digital images. The each digitalimage of the plurality of digital images includes a respective portionof a region of interest of a surface. The system includes means 920 fordetermining a substantial correspondence between (x) an extractedperceivable feature included in a border region segment of a selecteddigital image of the plurality of digital images and (y) an extracted atleast one respective perceivable feature included in each digital imageof the plurality of digital images other than the selected digitalimage. The system includes means 930 for gathering the determinedsubstantial correspondences for the extracted perceivable featureincluded in the border region segment of the selected digital image. Thesystem includes means 940 for generating data indicative of a borderregion-overlap status of the selected digital image. The data isgenerated at least partially in response to the gathered determinedsubstantial correspondences. The system includes means 950 for addingthe data indicative of the determined border region-overlap status forthe border region segment of the selected digital image to anomitted-coverage list. The system includes means 960 for iterativelydesignating a next digital image from the plurality of digital images asthe selected digital image until each digital image of the plurality ofdigital images has been designated. The system includes means 970 forinitiating a processing of each of the iteratively designated nextdigital images, the processing includes operations at means 920, 930,940, and 950. The system includes means 980 for identifying a particularportion of the region of interest as likely not included in theplurality of digital images (hereafter “possible non-imaged portion ofthe region of interest”). The identification of the possible non-imagedportion of the region of interest is at least partially based on theomitted-coverage list. The system includes means 990 for outputtinginformational data indicative of the possible non-imaged portion of theregion of interest.

FIG. 19 illustrates an environment 1200. The environment includes asurface of the skin 1201 of an individual human 1203, a handheld digitalimage acquisition device 1205 (illustrated as a camera), a plurality ofmedical skin images 1210, a system 1220, and the computing device 292having the screen 294 visible to the person 296.

The system 1220 includes a feature-detection circuit 1224 configured toextract at least one respective human-perceivable feature included ineach medical image of a plurality of medical images 1210 of the surfaceof the skin 1201 of an individual human 1203 (hereafter “medical skinimages”). The each medical image of plurality of medical skin imagesincludes a respective portion of a region of interest 1202 of thesurface of the skin of the individual human, and was acquired by thehandheld digital image acquisition device 1205. The system includes afeature-matching circuit 1228 configured to determine a substantialcorrespondence between (x) an extracted human-perceivable featureincluded in a border region segment of a selected medical skin image ofthe plurality of medical skin images and (y) an extracted at least onerespective human-perceivable feature included in the each medical skinimage of the plurality of medical skin images other than the selectedmedical skin image. The system includes a data collection circuit 1232configured to gather the determined substantial correspondences for thehuman-perceivable feature included in the border region segment of theselected medical skin image. The system includes a reporting circuit1236 configured to output informational data indicative of a possiblenon-imaged portion of the region of interest of the skin of theindividual human adjacent to the selected medical skin image. Theinformational data is responsive to an absence of a determinedsubstantial correspondence between the extracted human-perceivablefeature included in the border region segment of the selected medicalskin image and the extracted at least one respective feature included inthe each medical skin image of the plurality of medical skin imagesother than the selected medical skin image. In an embodiment, the systemincludes a processor 1250. In an embodiment, the processor may be atleast substantially similar to the processing unit 21 described inconjunction with FIG. 1. In an embodiment, the processor may be at leastsubstantially similar to the processor 120 described in conjunction withFIG. 2.

For example, a “medical skin image” may include a digital image of theskin of the individual human 1203 selected or captured by a health careprovider during a medical procedure or examination, or by the individual1203 during self-examination. The region of interest may have beenselected for any reason, including a possible disease state, or cosmeticreasons. Alternatively, the region of interest may have been selected bya machine. For example, a “medical skin image” may be of an exteriorskin surface, or an interior skin surface, such as the interior skinsurface of a colon or stomach. For example, a “medical skin image” mayinclude an image created using a technique or process for clinicalpurposes or medical science. For example, “a medical skin image” mayinclude an image produced using a technique or process involving lightin the visible, infrared, or ultraviolet spectrums. For example, a“medical skin image” may include an image that was acquired using atleast two wavelength energies and rendered visible to the human eyeusing an enhancement or augmentation technique. For example, thewavelength energies may include visible light, near infrared, infrared,or ultrasound.

For example, a perceivable feature may include a human-visionperceivable feature. For example, a human-vision perceivable feature mayinclude a feature that is visible to the naked eye or using naturalhuman vision, including corrective lenses. In an embodiment, aperceivable feature may include an augmented human-vision perceivablefeature, such as a feature visible to the naked eye as a result ofcomputer implemented enhancement, or computer augmented vision.

In an embodiment, the system 1220 includes an image receiver circuit1222 configured to receive the plurality of medical skin images 1210. Inan embodiment, the image receiver circuit includes an image receivercircuit configured to retrieve the plurality of medical skin imagesacquired by the handheld digital image acquisition device 1205 from amemory and/or storage device of a handheld digital image acquisitiondevice. For example, the image receiver circuit may be configured topull the plurality of medical skin images from a memory and/or storagedevice of the handheld digital image acquisition device. In anembodiment, the image receiver circuit includes an image receivercircuit configured to import from third-party device the plurality ofmedical skin images acquired by the handheld digital image acquisitiondevice. In an embodiment, the image receiver circuit includes an imagereceiver circuit configured to receive a push of the plurality ofmedical skin images from the handheld digital image acquisition device.In an embodiment, the plurality of medical skin images were acquiredduring an imaging session by the handheld digital image acquisitiondevice. For example, an imaging session may be a single session, or acombination of multiple sessions.

In an embodiment, the handheld digital image acquisition device 1205includes a handheld digital imaging device configured to capture theplurality of medical skin images. In an embodiment, the handheld digitalimage acquisition device includes a handheld digital image acquisitiondevice held by the individual human. In an embodiment, the handhelddigital image acquisition device includes a handheld digital imageacquisition device held and operated by a third-party human, illustratedas the human 296.

In an embodiment, the reporting circuit 1236 includes a reportingcircuit configured to output the informational data in substantiallyreal-time. In an embodiment, the reporting circuit includes a reportingcircuit configured in cooperation with the feature-detection circuit1224, the feature matching circuit 1228, and the data collection circuit1232 to output the informational data in substantially real-time. In anembodiment, substantially real-time includes while the handheld digitalimage acquisition device is in motion acquiring the plurality of medicalskin images. For example, in this embodiment, the system 1220 outputsthe informational data while additional medical skin images are beingacquired. Substantially real-time informational data is anticipated totimely inform the user of the handheld digital image acquisition deviceduring an image acquisition session of a possible non-imaged portion ofthe region of interest of the skin, and allow the user to position thehandheld digital image acquisition device and acquire a medical skinimage of the possible non-imaged portion before terminating the imageacquisition session. In an embodiment, substantially real-time includesless than approximately 30 minutes after the plurality of medical skinimages are received by the system. In an embodiment, substantiallyreal-time includes less than approximately 15 minutes after theplurality of medical skin images are received by the system. In anembodiment, substantially real-time includes less than approximately 6minutes after the plurality of medical skin images are received by thesystem. In an embodiment, substantially real-time includes less thanapproximately 2 minutes after the plurality of medical skin images arereceived by the system. In an embodiment, substantially real-timeincludes less than approximately 1 minute after the plurality of medicalskin images are received by the system. In an embodiment, substantiallyreal-time includes less than approximately 30 seconds after theplurality of medical skin images are received by the system.

In an embodiment, the system 1220 includes a border region detectioncircuit 1226 configured to detect a border region segment of a medicalskin image of the plurality of medical skin images. In an embodiment,the feature matching circuit 1228 includes a feature-matching circuitconfigured to determine a substantial correspondence between (x) anextracted human-perceivable feature included in a detected border regionsegment of a selected medical skin image of the plurality of medicalskin images and (y) an extracted at least one respectivehuman-perceivable feature included in the each medical skin image of theplurality of medical skin images other than the selected medical skinimage.

FIG. 20 illustrates an embodiment of a handheld digital imageacquisition device 1205 having image capture and image storagefunctionality. For example, the handheld digital acquisition device mayinclude a handheld digital camera, such as a handheld digital cameracommonly available on the consumer market, or an analog camera with adigital frame grabber. For example, the handheld digital acquisitiondevice may include a cellular phone having a built-in digital camera, ora smart phone having a built-in digital camera. For example, thehandheld digital acquisition device may include tablet computer, alaptop computer, a notebook computer, or the like and having a built-indigital camera.

The handheld digital image acquisition device 1205 includes a computingdevice (not shown), such as for example, the thin computing device 20described in conjunction with FIG. 1, that is operable to interact withfunctional elements of the handheld digital image acquisition device.The handheld digital image acquisition device also includes a pluralityof user interfaces 1320. The plurality of interfaces 1320 includes adisplay 1332. In alternative embodiments, the display may provide atextual, a visual display, and/or a graphical display. In a furtherembodiment, the display may include touch screen functionality operableto accept a user input. The plurality of user interfaces of the cameraalso includes a microphone 1334, a speaker 1338, and a plurality oftangible or virtual buttons 1344A-1344E. One or more of the tangible orvirtual buttons may include a light emitter, such as a light emittingdevice 1346A. Further, one or more of the tangible or virtual buttons1344A-1344E may include a vibrator operable to provide a tactiledisplay. The display 1332 and the tangible or virtual buttons1344A-1344E may have any functionality appropriate to the handhelddigital image acquisition device. For example, the button 1344E may beassigned to operate a camera element, such as a shutter function. Thebutton 1344A may be assigned an “enter” function, and buttons 1344B and1344C may be respectively assigned a scroll up and scroll down functionrelative to a menu displayed on the display 1332. The button 1344D maybe assigned to operate another camera element, such as a lens zoomfunction. The handheld digital image acquisition device also includescontext sensors 1350, which may be selected, for example, to producerelevant information about an environment extrinsic to the handhelddigital image acquisition device. The context sensors are illustrated asan external temperature sensor 1352 and a light intensity sensor 1354.The handheld digital image acquisition device further includes a USBport 1340, a network port 1342, and/or a wireless port (not shown).

In addition, the handheld digital image acquisition device 1205 includesa lens (not shown) and an image acquisition module (not shown). Theimage acquisition module controls the lens, a shutter, an aperture,and/or other elements as necessary to capture an image through the lens.In an embodiment, capturing images using a handheld digital imageacquisition device may be equated with photography as performed byconventional digital cameras. A captured image may be processed, stored,viewed, and/or distributed by the handheld digital image acquisitiondevice. The handheld digital image acquisition device also includes asystem memory (not shown), such as the system memory 22 of the thincomputing device 20 of FIG. 1. The system memory includes savedoperating systems and programs necessary to operate the handheld digitalimage acquisition device. In addition, the handheld digital imageacquisition device may include a computer readable media (not shown).The handheld digital image acquisition device may be configured tocapture still images, to capture streaming images, or to capture bothstill and streaming images.

The handheld digital image acquisition device 1205 includes operabilityto receive a user input through an interface of the plurality ofinterfaces 1320. For example, in an embodiment, detecting a user touchto the button 1344D may be received as an instruction and/or aselection. Another detected user touch to another user interface of theplurality of user interfaces 1320 may be received as another instructionand/or a selection. The user touch may be detected by a user interfacephysically incorporated in the handheld digital image acquisition device1205. In an alternative embodiment, a user input may be received bydetecting a signal responsive to a sound or voice received by themicrophone 1334. For example, a detection and recognition of a signalresponsive to a spoken command to the microphone 1334 may be received asan instruction to activate a program associated with the handhelddigital image acquisition device. Further, a detection of a signalresponsive to a sound or voice may be received by the microphone 1334.

Returning to FIG. 19, in an embodiment, the system 1220 includes anoverlap-analysis circuit 1234 configured to generate data indicative ofa border region-overlap status of the selected medical skin image. Thedata is generated at least partially in response to the gathereddetermined substantial correspondences between the extracted perceivablefeature included in the border region segment of the selected medicalskin image and the at least one respective perceivable feature includedin the each medical skin image of the plurality of medical skin imagesother than the selected medical skin image. In an embodiment, thereporting circuit includes a reporting circuit configured to outputinformational data indicative of the border region-overlap status of theselected medical skin image. The informational data is at leastpartially based on the data indicative of a border region-overlap statusof the selected medical skin image.

In an embodiment, the system 1220 is a standalone system, and notphysically incorporated within the handheld digital image acquisitiondevice 1205. In an embodiment, the standalone system is configured towirelessly communicate with the handheld digital image acquisitiondevice. In an embodiment, the system 1220 is physically incorporatedwithin the handheld digital image acquisition device 1205, for examplewithin the embodiment of the handheld digital image acquisition device1205 as illustrated in FIG. 20.

In an embodiment, the system 1220 includes computer-readable media 239configured to maintain the informational data indicative of the possiblenon-imaged portion of the region of interest adjacent to the selectedmedical skin image. In an embodiment, the system includes acommunication device configured to provide a notification at leastpartially based on the informational data to at least one of a human,computer, or system. For example, the communications device may beincorporated into the system as illustrated by the communication device1242. In another example, the communication device may be a third-partydevice in communication with the system as illustrated by the computingdevice 292 having the screen 294. In an embodiment, the system includesa communication device configured to display a human-perceivabledepiction of the informational data. In an embodiment, the systemincludes a communication device configured to output a signal usable indisplaying a human-perceivable depiction of the informational data. Forexample, the human-perceivable depiction may include an audio depictionof the informational data or a visual depiction of the informationaldata.

FIG. 21 illustrates an example operational flow 1500 implemented in acomputing device. After a start operation, the operational flow includesa feature-detection operation 1530. The feature-detection operationincludes extracting at least one respective human-perceivable featureincluded in each medical image of a plurality of medical images of theskin of an individual human (hereafter “medical skin images”). The eachmedical image of plurality of medical skin images includes a respectiveportion of a region of interest of a surface of the skin of theindividual human, and was acquired by a handheld digital imageacquisition device. In an embodiment, the feature-detection operationmay be implemented using the feature-detection circuit 1224 described inconjunction with FIG. 19. A matching operation 1540 includes determininga substantial correspondence between (x) an extracted human-perceivablefeature included in a border region segment of a selected medical skinimage of the plurality of medical skin images and (y) an extracted atleast one respective human-perceivable feature included in the eachmedical skin image of the plurality of medical skin images other thanthe selected medical skin image. In an embodiment, the matchingoperation may be implemented using the feature-matching circuit 1228described in conjunction with FIG. 19. A data collection operation 1550includes gathering the determined substantial correspondences for thehuman-perceivable feature included in the border region segment of theselected medical skin image. In an embodiment, the data collectionoperation may be implemented using the data collection circuit 1232described in conjunction with FIG. 19. A reporting operation 1560includes outputting informational data indicative of a possiblenon-imaged portion of the region of interest of the skin of theindividual human adjacent to the selected medical skin image. Theinformational data is responsive to an absence of a determinedsubstantial correspondence between the extracted human-perceivablefeature included in the border region segment of the selected medicalskin image and the extracted at least one respective feature included inthe each medical skin image of the plurality of medical skin imagesother than the selected medical skin image. In an embodiment, thereporting operation may be implemented using the reporting circuit 1236described in conjunction with FIG. 19. The operational flow includes anend operation.

FIG. 22 illustrates an alternative embodiment of the operational flow1500 of FIG. 21. In an embodiment, the operational flow includes anoperation 1510, which includes receiving the plurality of medical skinimages. In an embodiment, the operational flow includes an operation1520, which includes detecting the border region segment of a medicalskin image of the plurality of medical skin images. In an embodiment,the operational flow may include an operation 1575. The operation 1575includes iteratively designating a next medical skin image from theplurality of medical skin image as the selected medical skin image untileach medical skin image of the plurality of medical skin images has beendesignated. The operation 1575 also includes initiating a processing ofeach of the iteratively designated next medical skin image, theprocessing includes operations 1530, 1540, and 1550. In an embodiment,the operational flow may include at least one additional operation 1580.The at least one additional operation may include an operation 1582, anoperation 1584, or an operation 1586. The operation 1582 includesdisplaying the informational data. The operation 1584 includesmaintaining the informational data in computer-readable storage media.The operation 1586 includes providing a notification at least partiallybased on the informational data to at least one of a human, computer, orsystem.

FIG. 23 illustrates an alternative embodiment of the operational flow1500 of FIG. 21. In an embodiment, the operational flow may include atleast one additional operation, such as the operation 1570. Theoperation 1570 includes generating data indicative of a borderregion-overlap status of the selected medical skin image. The data isgenerated at least partially in response to the determined substantialcorrespondences between the human-perceivable feature included in theborder region segment of the selected medical skin image and theextracted at least one respective perceivable feature included in theeach medical skin image of the plurality of medical skin images otherthan the selected medical skin image. The operation 1570 may include atleast one additional operation, such as an operation 1572. The operation1572 includes generating data indicative of a possible non-imagedportion of the region of interest adjacent to the selected medical skinimage. The data is generated at least partially in response to thedetermined substantial correspondences between the extractedhuman-perceivable feature included in the border region segment of theselected medical skin image and the extracted at least one respectiveperceivable feature included in the each medical skin image of theplurality of medical skin images other than the selected medical skinimage.

In an embodiment, the reporting operation 1560 may include at least oneadditional operation. The at least one additional operation may includean operation 1562, an operation 1564, an operation 1566, an operation1568, or an operation 1569. The operation 1562 includes outputtinginformational data in substantially real time. The informational data isindicative of a possible non-imaged portion of the region of interest ofthe skin of the individual human adjacent to the selected medical skinimage. The operation 1564 includes outputting informational data isindicative of a possible non-imaged portion of the region of interest ofthe skin of the individual human adjacent to the selected medical skinimage. The informational data is at least partially based on the dataindicative of a border region-overlap status of the selected medicalskin image. The operation 1566 includes outputting informational dataindicative of a possible non-imaged portion of the region of interestadjacent to the selected medical skin image. The informational data isat least partially based on the data indicative of a possible non-imagedportion of the region of interest adjacent to the selected medical skinimage. The operation 1568 includes outputting informational data usablein displaying a human-perceivable indication of a possible non-imagedportion of the region of interest of the surface. The operation 1569includes transforming the informational data into a particular visualdepiction of a possible non-imaged portion of the region of interest ofthe surface, and outputting the transformed informational data. Forexample, the particular visual depiction may include a depiction of alocation of the possible non-imaged portion of the region of interest ora bearing of the possible non-imaged portion of the region of interestrelative to a determinable location.

FIG. 24 illustrates an alternative embodiment of the operational flow1500 of FIG. 21. In an embodiment, the operational flow may include atleast one additional operation, such as the operational flow 1590. Theoperational flow 1590 includes an operation 1591, an operation 1593, anoperation 1596, and an operation 1598. The operation 1591 includesextracting at least one human-perceivable feature included in afollow-on medical image of the skin of the individual human (hereafter“follow-on medical skin image”). The follow-on medical skin imageincludes an image of a portion of the region of interest of the surfaceof the skin of the individual human, and was acquired by the handhelddigital image acquisition device subsequent to the acquisition of theplurality of medical skin images. For example, a follow-on medical imagemay include a medical image acquired subsequent to acquisition of theplurality of medical images. For example, a follow-on medical image mayinclude a medical image acquired as a consequence of the informationaldata outputted in operation 1560. For example, a follow-on medical imagemay include a medical image that follows something else as a consequenceor natural development, such as a follow-up. The operation 1593 includesdetermining a substantial correspondence between (x) an extractedhuman-perceivable feature included in a border region segment of thefollow-on medical skin image and (y) an extracted at least onehuman-perceivable feature included in the selected medical skin image.The operation 1596 includes gathering the determined substantialcorrespondence for the border region segment of the follow-on medicalskin image. The operation 1598 includes outputting updated informationaldata indicative of a possible non-imaged portion of the region ofinterest of the skin of the individual human adjacent to the selectedmedical skin image. The informational data is responsive to an absenceof a determined substantial correspondence for the border region segmentof the follow-on medical skin image.

In an embodiment, the operation 1593 may include at least one additionaloperation, such as an operation 1594. The operation 1594 includesdetermining a substantial correspondence between (x) an extractedhuman-perceivable feature included in a border region segment of thefollow-on medical skin image and (y) an extracted at least onerespective human-perceivable feature included in the each medical skinimage of the plurality of medical skin images.

FIG. 25 illustrates an example computer program product 1600. Thecomputer program product includes computer-readable media 1610 bearingprogram instructions 1620. The program instructions, when executed by aprocessor of a computing device, cause the computing device to perform aprocess. The process includes extracting at least one respectivehuman-perceivable feature included in each medical image of a pluralityof medical images of the skin of an individual human (hereafter “medicalskin images”). The each medical image of plurality of medical skinimages includes a respective portion of a region of interest of asurface of the skin of the individual human, and was acquired by ahandheld digital image acquisition device. The process includesdetermining a substantial correspondence between (x) an extractedhuman-perceivable feature included in a border region segment of aselected medical skin image of the plurality of medical skin images and(y) an extracted at least one respective human-perceivable featureincluded in the each medical skin image of the plurality of medical skinimages other than the selected medical skin image. The process includesgathering the determined substantial correspondences for the borderregion segment of the selected medical skin image. The process includesoutputting informational data indicative of a possible non-imagedportion of the region of interest of the skin of the individual humanadjacent to the selected medical skin image. The informational dataresponsive to an absence of a determined substantial correspondencebetween the extracted human-perceivable feature included in the borderregion segment of the selected medical skin image and the extracted atleast one respective feature included in the each medical skin image ofthe plurality of medical skin images other than the selected medicalskin image.

In an embodiment, the computer-readable media includes a tangiblecomputer-readable media 1612. In an embodiment, the computer-readablemedia includes a communications media 1614.

FIG. 26 illustrates an alternative embodiment of the computer programproduct 1600 of FIG. 24. In an embodiment, the process includes 1622receiving the plurality of medical skin images. In an embodiment, theprocess includes 1624 detecting a border region segment of a medicalskin image of the plurality of medical skin images. In an embodiment,the process includes 1626 displaying the informational data. In anembodiment, the process includes 1628 maintaining the informational datain computer-readable storage media.

FIG. 27 illustrates an example system 1700. The example system includesmeans 1710 for extracting at least one respective human-perceivablefeature included in each medical image of a plurality of medical imagesof the skin of an individual human (hereafter “medical skin images”).The each medical image of plurality of medical skin images includes arespective portion of a region of interest of a surface of the skin ofthe individual human, and was acquired by a handheld digital imageacquisition device. The system includes means 1720 for determining asubstantial correspondence between (x) an extracted human-perceivablefeature included in a border region segment of a selected medical skinimage of the plurality of medical skin images and (y) an extracted atleast one respective human-perceivable feature included in the eachmedical skin image of the plurality of medical skin images other thanthe selected medical skin image. The system includes means 1730 forgathering the determined substantial correspondences for the borderregion segment of the selected medical skin image. The system includesmeans 1740 for outputting informational data indicative of a possiblenon-imaged portion of the region of interest of the skin of theindividual human adjacent to the selected medical skin image. Theinformational data responsive to an absence of a determined substantialcorrespondence between the extracted human-perceivable feature includedin the border region segment of the selected medical skin image and theextracted at least one respective feature included in the each medicalskin image of the plurality of medical skin images other than theselected medical skin image.

FIG. 28 illustrates an example environment 1800. The example environmentincludes the surface of the skin 1201, the handheld digital imageacquisition device 1205, the plurality of medical skin images 1210, asystem 1820, and the computing device 292 having the screen 294 visibleto the person 296.

The system 1820 includes a feature-detection circuit 1824 configured toextract at least one respective human-perceivable feature included ineach medical image of a plurality of medical images 1210 of the surfaceof the skin 1201 of an individual human 1203 (hereafter “medical skinimages”). The each medical image of plurality of medical skin imagesincludes a respective portion of the region of interest 1202 of asurface of the skin of the individual human, and was acquired by thehandheld digital image acquisition device 1205. The system includes afeature matching circuit 1828 configured to determine a substantialcorrespondence between (x) an extracted human-perceivable featureincluded in a border region segment of a selected medical skin image ofthe plurality of medical skin images and (y) an extracted at least onerespective human-perceivable feature included in the each medical skinimage of the plurality of medical skin images other than the selectedmedical skin image. The system includes a data collection circuit 1832configured to gather the determined substantial correspondences for theextracted human-perceivable feature included in the border regionsegment of the selected medical skin image.

The system 1820 includes an overlap-analysis circuit 1834 configured togenerate data indicative of a border region-overlap status of theselected medical skin image. The data is generated at least partially inresponse to the determined substantial correspondences. The systemincludes a list management circuit 1836 configured to add the dataindicative of the determined border region-overlap status for the borderregion segment of the selected medical skin image to an omitted-coveragelist. The system includes an iteration control circuit 1838 configuredto iteratively designate a next medical skin image from the plurality ofmedical skin images as the selected medical skin image until eachmedical skin image of the plurality of medical skin images has beendesignated. The iteration control circuit is also configured to initiatea processing of each of the iteratively designated next medical skinimages by the feature-matching circuit 1828, the data collection circuit1832, the overlap-analysis circuit 1834, and the list management circuit1836. The system includes a coverage-analysis circuit 1844 configured toidentify a particular portion of the skin surface as likely not includedin the plurality of medical skin images (hereafter “possible non-imagedportion of the region of interest”). The identification of the possiblenon-imaged portion of the region of interest 1202 is at least partiallybased on the omitted-coverage list. The system includes a reportingcircuit 1846 configured to output user-assistance information at leastpartially based on the identified possible non-imaged portion of theskin.

In an embodiment, the system 1820 includes an image receiver circuit1822 configured to receive the plurality of medical skin images 1210. Inan embodiment, the system includes a border region detection circuit1826 configured to detect a border region segment of a medical skinimage of the plurality of medical skin images.

In an embodiment, the coverage-analysis circuit 1844 includes acoverage-analysis circuit configured to identify a particular portion ofthe surface of the skin 1201 as likely not included in the plurality ofmedical skin images 1210 (hereafter “possible non-imaged portion of theskin”) and to identify at least one medical skin image of the pluralityof medical skin images as spatially proximate to the possible non-imagedportion of the region of interest 1202 (hereafter “signpost medical skinimage”). The identification of the possible non-imaged portion of theskin and the identification of the signpost medical skin image is atleast partially based on the omitted-coverage list. In an embodiment,the reporting circuit 1846 includes a reporting circuit configured tooutput user-assistance information indicative of the possible non-imagedportion of the region of interest adjacent to the selected medical skinimage and indicative of the signpost medical skin image.

In an embodiment, the coverage-analysis circuit 1844 includes acoverage-analysis circuit configured to identify a particular portion ofthe region of interest 1202 as likely not included in the plurality ofmedical skin images 1210 (hereafter “possible non-imaged portion of theregion of interest”). The identification of the possible non-imagedportion of the region of interest at least partially based on theomitted-coverage list. The coverage-analysis circuit is configured toidentify at least three medical skin images of the plurality of medicalskin images immediately adjacent to the possible non-imaged portion ofthe region of interest. The identification of the at least three medicalskin images is at least partially based on the omitted-coverage list.The coverage analysis circuit is configured to define a substantiallysimple closed curve. The coverage-analysis circuit is configured todetermine whether the possible non-imaged portion of the region ofinterest lies inside or outside of the region of interest, Thedetermination is at least partially based on the positions of theidentified at least three medical skin images relative to the closedcurve. For example, see description in conjunction with FIG. 13.Continuing with reference to FIG. 28, in an embodiment, the reportingcircuit 1846 includes a reporting circuit configured to outputuser-assistance information indicative of the identified possiblenon-imaged portion of the region of interest and indicative of thedetermination whether the possible non-imaged portion of the region ofinterest lies inside or outside of the region of interest.

In an embodiment of the system 1820, the user-assistance informationincludes a user-assistance corresponding to a location of the possiblenon-imaged portion of the region of interest 1202. In an embodiment ofthe system, the user-assistance information includes user-assistanceinformation corresponding to spatially orientating the handheld digitalimage acquisition device 1205 in an alignment to acquire a medical skinimage of the possible non-imaged portion of the region of interest. Inan embodiment of the system, the user-assistance information includesuser-assistance information corresponding to selecting a parameterfacilitating an acquisition of a medical skin image of the possiblenon-imaged portion of the region of interest. For example, the parametermay include a magnification, orientation, alignment, or lightingfacilitating an acquisition of a medical skin image. In an embodiment ofthe system, the user-assistance information includes user-assistancecorresponding to initiating an acquisition by a user-held digital imageacquisition device of a medical skin image. In an embodiment, theuser-assistance information includes user instructions corresponding tooperating the user-held digital image acquisition device in acquiring amedical skin image. In an embodiment, the user-assistance informationincludes user-assistance responsive to a request entered by the user inconjunction with acquiring a medical skin image of the possiblenon-imaged portion of the region of interest. For example, the requestentered by the user may be based upon a menu of availableuser-assistances.

In an embodiment, the system 1820 includes computer-readable media 239configured to maintain the user-assistance information corresponding tothe identified possible non-imaged portion of the region of interest1202 and to the signpost medical skin image.

In an embodiment, the reporting circuit 1846 includes a reportingcircuit configured to output user-assistance information insubstantially real-time. The user-assistance information is at leastpartially based on the identified possible non-imaged portion of thesurface of the skin 1201. In an embodiment, the reporting circuitincludes a reporting circuit configured to output user-assistanceinformation usable in displaying a human-perceivable indication of thepossible non-imaged portion of the region of interest of the surface. Inan embodiment, the reporting circuit includes a reporting circuitconfigured to output a rendering of the user-assistance information in aform facilitating a human-perceivable representation of theuser-assistance information. For example, the rendering may include apre-rendered user-assistance information. For example, the rendering mayinclude an optimized representation of the user-assistance information.For example, the rendering may include a rendering of theuser-assistance information structured in a format facilitating ahuman-perceivable representation of the user-assistance information. Forexample, the rendering may include a rendering of the user-assistanceinformation in a form facilitating a human-vision perceivablerepresentation or an augmented human-vision perceivable representationof the user-assistance information.

In an embodiment, the system 1820 includes the computer-readable media239 configured to maintain the user-assistance information correspondingto the identified possible non-imaged portion of the region of interest1202 and to the signpost medical skin image. In an embodiment, thesystem includes a communications device configured to display aparticular human-perceivable depiction of the user-assistanceinformation. For example, the communication device may include thecommunications device 1842. For example, the communications device mayinclude a display of the handheld digital image acquisition device 1205.For example, the communication device may be a third-party device incommunication with the system as illustrated by the computing device 292having the screen 294. For example, the human-perceivable depiction mayinclude a visual or an audio human-perceivable depiction of theuser-assistance information. In an embodiment, the system includes aprocessor 1850. In an embodiment, the processor may be at leastsubstantially similar to the processing unit 21 described in conjunctionwith FIG. 1. In an embodiment, the processor may be at leastsubstantially similar to the processor 120 described in conjunction withFIG. 2.

FIG. 29 illustrates an example operational flow 1900 implemented in acomputing device. After a start operation, the operational flow includesa detection operation 1930. The detection operation includes extractingat least one respective human-perceivable feature included in eachmedical image of a plurality of medical images of the skin of anindividual human (hereafter “medical skin images”). The each medicalimage of plurality of medical skin images includes a respective portionof a region of interest of a surface of the skin of the individualhuman, and was acquired by a handheld digital image acquisition device.In an embodiment, the detection operation may be implemented using thefeature-detection circuit 1824 described in conjunction with FIG. 28. Afeature matching operation 1940 includes determining a substantialcorrespondence between (x) an extracted human-perceivable featureincluded in a border region segment of a selected medical skin image ofthe plurality of medical skin images and (y) an extracted at least onerespective human-perceivable feature included in each medical skin imageof the plurality of medical skin images other than the selected medicalskin image. In an embodiment, the feature matching operation may beimplemented using the feature matching circuit 1828 described inconjunction with FIG. 28. A data collection operation 1950 includesgathering the determined substantial correspondences for the extractedhuman-perceivable feature included in the border region segment of theselected medical skin image. In an embodiment, the data collectionoperation may be implemented using the data collection circuit 1832described in conjunction with FIG. 28.

An overlap-analysis operation 1960 includes generating data indicativeof a border region-overlap status of the selected medical skin image.The data is generated at least partially in response to the determinedsubstantial correspondences. In an embodiment, the overlap-analysisoperation may be implemented using the overlap-analysis circuit 1834described in conjunction with FIG. 28. A list management operation 1965includes adding the data indicative of the determined borderregion-overlap status for the border region segment of the selectedmedical skin image to an omitted-coverage list. In an embodiment, thelist management operation may be implemented using the list managementcircuit 1836 described in conjunction with FIG. 28. A next-imageselection operation 1970 includes iteratively designating a next medicalskin image from the plurality of medical skin images as the selectedmedical skin image until each medical skin image of the plurality ofmedical skin images has been designated. In an embodiment, thenext-image selection operation may be implemented using the iterationcontrol circuit 1838 described in conjunction with FIG. 28. An iterationoperation 1975 includes processing of each of the iteratively designatednext medical skin images by operations 1940, 1950, 1960, and 1965. In anembodiment, the iteration operation may also be implemented using theiteration control circuit 1838 described in conjunction with FIG. 28.

A coverage-analysis operation 1980 includes identifying a particularportion of the skin surface as likely not included in the plurality ofmedical skin images (hereafter “possible non-imaged portion of theskin”). The identifying the possible non-imaged portion of the skin isat least partially based on the omitted-coverage list. In an embodiment,the coverage-analysis operation may be implemented using thecoverage-analysis circuit 1844 described in conjunction with FIG. 28. Areporting operation 1985 includes outputting user-assistance informationat least partially based on the identified possible non-imaged portionof the skin. In an embodiment, the reporting operation may beimplemented using the reporting circuit 1846 described in conjunctionwith FIG. 28. The operational flow includes an end operation.

FIG. 30 illustrates an alternative embodiment of the operational flow1900 of FIG. 29. In an embodiment, the operational flow includes anoperation 1910. The operation 1910 includes receiving the plurality ofmedical skin images. In an embodiment, the operational flow includes anoperation 1920. The operation 1920 includes detecting a border regionsegment of a medical skin image of the plurality of medical skin images.In an embodiment, the reporting operation 1985 may include at least oneadditional operation. The at least one additional operation may includean operation 1986, an operation 1987, or an operation 1988. Theoperation 1986 includes outputting user-assistance information insubstantially real-time and at least partially based on the identifiedpossible non-imaged portion of the skin. The operation 1987 includesoutputting user-assistance information usable in displaying ahuman-perceivable indication of the possible non-imaged portion of theregion of interest of the surface. The operation 1988 includestransforming the user-assistance information into a particular visualdepiction of a possible non-imaged portion of the region of interest ofthe surface, and outputting the transformed user-assistance information.In an embodiment, the operational flow includes a storage operation1990. The storage operation 1990 includes maintaining theuser-assistance information in computer-readable storage media. In anembodiment, the storage operation may be implemented using thecomputer-readable media 239 described in conjunction with FIG. 28.

FIG. 31 illustrates an example computer program product 2000. Thecomputer program product includes computer-readable media 2010 bearingprogram instructions 2020. The program instructions, when executed by aprocessor of a computing device, cause the computing device to perform aprocess. The process includes (i) extracting at least one respectivehuman-perceivable feature included in each medical image of a pluralityof medical images of the skin of an individual human (hereafter “medicalskin images”). The each medical image of plurality of medical skinimages includes a respective portion of a region of interest of asurface of the skin of the individual human, and was acquired by ahandheld digital image acquisition device. The process includes (ii)determining a substantial correspondence between (x) an extractedhuman-perceivable feature included in a border region segment of aselected medical skin image of the plurality of medical skin images and(y) an extracted at least one respective human-perceivable featureincluded in each medical skin image of the plurality of medical skinimages other than the selected medical skin image. The process includes(iii) gathering the determined substantial correspondences for theextracted human-perceivable feature included in the border regionsegment of the selected medical skin image. The process includes (iv)generating data indicative of a border region-overlap status of theselected medical skin image. The data is generated at least partially inresponse to the determined substantial correspondences. The processincludes (v) adding the data indicative of the determined borderregion-overlap status for the border region segment of the selectedmedical skin image to an omitted-coverage list. The process includes(vi) iteratively designating a next medical skin image from a pluralityof medical skin images as the selected medical skin image until eachmedical skin image of the plurality of medical skin images has beendesignated. The process includes (vii) processing of each of theiteratively designated next medical skin images, the processing includesoperations (ii), (iii), (iv), and (v). The process includes (viii)identifying a particular portion of the skin surface as likely notincluded in the plurality of medical skin images (hereafter “possiblenon-imaged portion of the skin”). The identifying the possiblenon-imaged portion of the skin is at least partially based on theomitted-coverage list. The process includes (ix) outputtinguser-assistance information at least partially based on the identifiedpossible non-imaged portion of the skin.

In an embodiment, the computer-readable media 2010 includes tangiblecomputer-readable media 2012. In an embodiment, the computer-readablemedia includes communications media 2014.

FIG. 32 illustrates an alternative embodiment of the computer programproduct 2000 of FIG. 31. In an embodiment, the process includes 2022receiving the plurality of medical skin images. In an embodiment, theprocess includes 2024 detecting a border region segment of a medicalskin image of the plurality of medical skin images. In an embodiment,the process includes 2026 displaying the user-assistance information. Inan embodiment, the process includes 2028 maintaining the user-assistanceinformation in computer-readable storage media. In an embodiment, theprocess includes (i) outputting user-assistance information includes2029 outputting user-assistance information in substantially real timeand at least partially based on the identified possible non-imagedportion of the skin.

FIG. 33 illustrates an example system 2100. The system includes means2110 for extracting at least one respective human-perceivable featureincluded in each medical image of a plurality of medical images of theskin of an individual human (hereafter “medical skin images”). The eachmedical image of the plurality of medical skin images includes arespective portion of a region of interest of a surface of the skin ofthe individual human, and was acquired by a handheld digital imageacquisition device. The system includes means 2120 for determining asubstantial correspondence between (x) an extracted human-perceivablefeature included in a border region segment of a selected medical skinimage of the plurality of medical skin images and (y) an extracted atleast one respective human-perceivable feature included in each medicalskin image of the plurality of medical skin images other than theselected medical skin image. The system includes means 2130 forgathering the determined substantial correspondences for the extractedhuman-perceivable feature included in the border region segment of theselected medical skin image. The system includes means 2140 forgenerating data indicative of a border region-overlap status of theselected medical skin image. The data is generated at least partially inresponse to the determined substantial correspondences. The systemincludes means 2150 for adding the data indicative of the determinedborder region-overlap status for the border region segment of theselected medical skin image to an omitted-coverage list. The systemincludes means 2160 for iteratively designating a next medical skinimage from the plurality of medical skin images as the selected medicalskin image until each medical skin image of the plurality of medicalskin images has been designated. The system includes means 2170 meansfor initiating a processing of each of the iteratively designated nextmedical skin images by means 2120, 2130, 2140, and 2150. The systemincludes means 2180 for identifying a particular portion of the skinsurface as likely not included in the plurality of medical skin images(hereafter “possible non-imaged portion of the skin”). The identifyingthe possible non-imaged portion of the skin is at least partially basedon the omitted-coverage list. The system includes means 2190 foroutputting user-assistance information at least partially based on theidentified possible non-imaged portion of the skin.

In an alternative embodiment, the means 2190 includes means 2192 foroutputting user-assistance information in substantially real-time and atleast partially based on the identified possible non-imaged portion ofthe skin.

All references cited herein are hereby incorporated by reference intheir entirety or to the extent their subject matter is not otherwiseinconsistent herewith.

In some embodiments, “configured” includes at least one of designed, setup, shaped, implemented, constructed, or adapted for at least one of aparticular purpose, application, or function.

It will be understood that, in general, terms used herein, andespecially in the appended claims, are generally intended as “open”terms. For example, the term “including” should be interpreted as“including but not limited to.” For example, the term “having” should beinterpreted as “having at least.” For example, the term “has” should beinterpreted as “having at least.” For example, the term “includes”should be interpreted as “includes but is not limited to,” etc. It willbe further understood that if a specific number of an introduced claimrecitation is intended, such an intent will be explicitly recited in theclaim, and in the absence of such recitation no such intent is present.For example, as an aid to understanding, the following appended claimsmay contain usage of introductory phrases such as “at least one” or “oneor more” to introduce claim recitations. However, the use of suchphrases should not be construed to imply that the introduction of aclaim recitation by the indefinite articles “a” or “an” limits anyparticular claim containing such introduced claim recitation toinventions containing only one such recitation, even when the same claimincludes the introductory phrases “one or more” or “at least one” andindefinite articles such as “a” or “an” (e.g., “a receiver” shouldtypically be interpreted to mean “at least one receiver”); the sameholds true for the use of definite articles used to introduce claimrecitations. In addition, even if a specific number of an introducedclaim recitation is explicitly recited, it will be recognized that suchrecitation should typically be interpreted to mean at least the recitednumber (e.g., the bare recitation of “at least two chambers,” or “aplurality of chambers,” without other modifiers, typically means atleast two chambers).

In those instances where a phrase such as “at least one of A, B, and C,”“at least one of A, B, or C,” or “an [item] selected from the groupconsisting of A, B, and C,” is used, in general such a construction isintended to be disjunctive (e.g., any of these phrases would include butnot be limited to systems that have A alone, B alone, C alone, A and Btogether, A and C together, B and C together, or A, B, and C together,and may further include more than one of A, B, or C, such as A₁, A₂, andC together, A, B₁, B₂, C₁, and C₂ together, or B₁ and B₂ together). Itwill be further understood that virtually any disjunctive word or phrasepresenting two or more alternative terms, whether in the description,claims, or drawings, should be understood to contemplate thepossibilities of including one of the terms, either of the terms, orboth terms. For example, the phrase “A or B” will be understood toinclude the possibilities of “A” or “B” or “A and B.”

The herein described aspects depict different components containedwithin, or connected with, different other components. It is to beunderstood that such depicted architectures are merely examples, andthat in fact many other architectures can be implemented which achievethe same functionality. In a conceptual sense, any arrangement ofcomponents to achieve the same functionality is effectively “associated”such that the desired functionality is achieved. Hence, any twocomponents herein combined to achieve a particular functionality can beseen as “associated with” each other such that the desired functionalityis achieved, irrespective of architectures or intermedial components.Likewise, any two components so associated can also be viewed as being“operably connected,” or “operably coupled,” to each other to achievethe desired functionality. Any two components capable of being soassociated can also be viewed as being “operably couplable” to eachother to achieve the desired functionality. Specific examples ofoperably couplable include but are not limited to physically mateable orphysically interacting components or wirelessly interactable orwirelessly interacting components.

With respect to the appended claims the recited operations therein maygenerally be performed in any order. Also, although various operationalflows are presented in a sequence(s), it should be understood that thevarious operations may be performed in other orders than those which areillustrated, or may be performed concurrently. Examples of suchalternate orderings may include overlapping, interleaved, interrupted,reordered, incremental, preparatory, supplemental, simultaneous,reverse, or other variant orderings, unless context dictates otherwise.Use of “Start,” “End,” “Stop,” or the like blocks in the block diagramsis not intended to indicate a limitation on the beginning or end of anyoperations or functions in the diagram. Such flowcharts or diagrams maybe incorporated into other flowcharts or diagrams where additionalfunctions are performed before or after the functions shown in thediagrams of this application. Furthermore, terms like “responsive to,”“related to,” or other past-tense adjectives are generally not intendedto exclude such variants, unless context dictates otherwise.

While various aspects and embodiments have been disclosed herein, otheraspects and embodiments will be apparent to those skilled in the art.The various aspects and embodiments disclosed herein are for purposes ofillustration and are not intended to be limiting, with the true scopeand spirit being indicated by the following claims.

What is claimed is:
 1. A system comprising: (a) a feature-detectioncircuit configured to extract at least one respective human-perceivablefeature included in each medical image of a plurality of medical imagesof the skin of an individual human (hereafter “medical skin images”),the each medical image of plurality of medical skin images includes arespective portion of a region of interest of a surface of the skin ofthe individual human, and was acquired by a handheld digital imageacquisition device; (b) a feature-matching circuit configured todetermine a substantial correspondence between (x) an extractedhuman-perceivable feature included in a border region segment of aselected medical skin image of the plurality of medical skin images and(y) an extracted at least one respective human-perceivable featureincluded in the each medical skin image of the plurality of medical skinimages other than the selected medical skin image; (c) a data collectioncircuit configured to gather the determined substantial correspondencesfor the extracted human-perceivable feature included in the borderregion segment of the selected medical skin image; (d) anoverlap-analysis circuit configured to generate data indicative of aborder region-overlap status of the selected medical skin image, thedata generated at least partially in response to the determinedsubstantial correspondences; (e) a list management circuit configured toadd the data indicative of the determined border region-overlap statusfor the border region segment of the selected medical skin image to anomitted-coverage list; (f) an iteration control circuit configured toiteratively designate a next medical skin image from the plurality ofmedical skin images as the selected medical skin image until eachmedical skin image of the plurality of medical skin images has beendesignated, and initiate a processing of each of the iterativelydesignated next medical skin images by the feature-matching circuit, thedata collection circuit, the overlap-analysis circuit, and the listmanagement circuit; (g) a coverage-analysis circuit configured toidentify a particular portion of the skin surface as likely not includedin the plurality of medical skin images (hereafter “possible non-imagedportion of the region of interest”), the identifying the possiblenon-imaged portion of the region of interest at least partially based onthe omitted-coverage list; and (h) a reporting circuit configured tooutput user-assistance information at least partially based on theidentified possible non-imaged portion of the skin.
 2. The system ofclaim 1, further comprising: an image receiver circuit configured toreceive the plurality of medical skin images.
 3. The system of claim 1,further comprising: a border region detection circuit configured todetect at least one border region segment of a medical skin image of theplurality of medical skin images.
 4. The system of claim 1, wherein thecoverage-analysis circuit includes: a coverage-analysis circuitconfigured to identify a particular portion of the skin surface aslikely not included in the plurality of medical skin images (hereafter“possible non-imaged portion of the skin”) and to identify at least onemedical skin image of the plurality of medical skin images as spatiallyproximate to the possible non-imaged portion of the region of interest(hereafter “signpost medical skin image”), the identifying the possiblenon-imaged portion of the skin and the identifying the signpost medicalskin image at least partially based on the omitted-coverage list.
 5. Thesystem of claim 4, wherein the reporting circuit includes: a reportingcircuit configured to output user-assistance information indicative ofthe possible non-imaged portion of the region of interest adjacent tothe selected medical skin image and of the signpost medical skin image.6. The system of claim 1, wherein the coverage-analysis circuitincludes: a coverage-analysis circuit configured to (i) identify aparticular portion of the region of interest of a surface as likely notincluded in the plurality of medical skin images (hereafter “possiblenon-imaged portion of the region of interest”), the identifying thepossible non-imaged portion of the region of interest at least partiallybased on the omitted-coverage list; (ii) identify at least three medicalskin images of the plurality of medical skin images immediately adjacentto the possible non-imaged portion of the region of interest, theidentifying the at least three medical skin images at least partiallybased on the omitted-coverage list; (iii) define a substantially simpleclosed curve formed by linking at least one border region segment ofeach of the at least three identified medical skin images wherein theborder region segments each have an overlap status of likely notoverlapped; and (iv) determine whether the possible non-imaged portionof the region of interest lies inside or outside of the region ofinterest, the determination at least partially based on the positions ofthe identified at least three medical skin images relative to the closedcurve.
 7. The system of claim 6, wherein the reporting circuit includes:a reporting circuit configured to output user-assistance informationindicative of the identified possible non-imaged portion of the regionof interest and indicative of the determination whether the possiblenon-imaged portion of the region of interest lies inside or outside ofthe region of interest.
 8. The system of claim 1, wherein theuser-assistance information includes a user-assistance informationcorresponding to a location of the possible non-imaged portion of theregion of interest.
 9. The system of claim 1, wherein theuser-assistance information includes user-assistance informationcorresponding to spatially orientating the handheld digital imageacquisition device in an alignment to acquire a medical skin image ofthe possible non-imaged portion of the region of interest.
 10. Thesystem of claim 1, wherein the user-assistance information includesuser-assistance information corresponding to selecting a parameterfacilitating an acquisition of a medical skin image of the possiblenon-imaged portion of the region of interest.
 11. The system of claim 1,wherein the user-assistance information includes user-assistanceinformation corresponding to initiating an acquisition by the handhelddigital image acquisition device of a medical skin image of the possiblenon-imaged portion of the region of interest.
 12. The system of claim 1,wherein the user-assistance information includes user instructionscorresponding to operating the handheld digital image acquisition devicein acquiring a medical skin image of the possible non-imaged portion ofthe region of interest.
 13. The system of claim 1, wherein theuser-assistance information includes user-assistance informationresponsive to a request entered by the user in conjunction withacquiring a medical skin image of the possible non-imaged portion of theregion of interest.
 14. The system of claim 1, wherein the reportingcircuit includes: a reporting circuit configured to outputuser-assistance information in substantially real-time, theuser-assistance information at least partially based on the identifiedpossible non-imaged portion of the surface of the skin.
 15. The systemof claim 1, wherein the reporting circuit includes: a reporting circuitconfigured to output user-assistance information usable in displaying ahuman-perceivable indication of the possible non-imaged portion of theregion of interest of the surface of the skin.
 16. The system of claim1, wherein the reporting circuit includes: a reporting circuitconfigured to output a rendering of the user-assistance information in aform facilitating a human-perceivable representation of theuser-assistance information.
 17. The system of claim 1, furthercomprising: a communications device configured to display a particularhuman-perceivable depiction of the user-assistance information.
 18. Amethod implemented in a computing device, the method comprising: (a)extracting at least one respective human-perceivable feature included ineach medical image of a plurality of medical images of the skin of anindividual human (hereafter “medical skin images”), the each medicalimage of plurality of medical skin images includes a respective portionof a region of interest of a surface of the skin of the individualhuman, and was acquired by a handheld digital image acquisition device;(b) determining a substantial correspondence between (x) an extractedhuman-perceivable feature included in a border region segment of aselected medical skin image of the plurality of medical skin images and(y) an extracted at least one respective human-perceivable featureincluded in each medical skin image of the plurality of medical skinimages other than the selected medical skin image; (c) gathering thedetermined substantial correspondences for the extractedhuman-perceivable feature included in the border region segment of theselected medical skin image; (d) generating data indicative of a borderregion-overlap status of the selected medical skin image, the datagenerated at least partially in response to the determined substantialcorrespondences; (e) adding the data indicative of the determined borderregion-overlap status for the border region segment of the selectedmedical skin image to an omitted-coverage list; (f) iterativelydesignating a next medical skin image from the plurality of medical skinimages as the selected medical skin image until each medical skin imageof the plurality of medical skin images has been designated; (g)processing of each of the iteratively designated next medical skinimages, the processing including operations (b), (c), (d), and (e); (h)identifying a particular portion of the skin surface as likely notincluded in the plurality of medical skin images (hereafter “possiblenon-imaged portion of the skin”), the identifying the possiblenon-imaged portion of the skin at least partially based on theomitted-coverage list; and (i) outputting user-assistance information atleast partially based on the identified possible non-imaged portion ofthe skin.
 19. The method of claim 18, wherein the outputtinguser-assistance information includes: outputting user-assistanceinformation in substantially real-time and at least partially based onthe identified possible non-imaged portion of the skin.
 20. The methodof claim 18, wherein the outputting user-assistance informationincludes: outputting user-assistance information usable in displaying ahuman-perceivable indication of the possible non-imaged portion of theregion of interest of the surface.
 21. The method of claim 18, whereinthe outputting user-assistance information includes: transforming theuser-assistance information into a particular visual depiction of apossible non-imaged portion of the region of interest of the surface,and outputting the transformed user-assistance information.
 22. Themethod of claim 18, further comprising: receiving the plurality ofmedical skin images.
 23. The method of claim 18, further comprising:detecting the border region segment of a medical skin image of theplurality of medical skin images.
 24. The method of claim 18, furthercomprising: maintaining the user-assistance information incomputer-readable storage media.
 25. A computer program productcomprising: (a) a non-transitory computer-readable medium storingprogram instructions thereon which, when executed by a processor of acomputing device, cause the computing device to perform a processincluding: (i) extracting at least one respective human-perceivablefeature included in each medical image of a plurality of medical imagesof the skin of an individual human (hereafter “medical skin images”),the each medical image of plurality of medical skin images includes arespective portion of a region of interest of a surface of the skin ofthe individual human, and was acquired by a handheld digital imageacquisition device; (ii) determining a substantial correspondencebetween (x) an extracted human-perceivable feature included in a borderregion segment of a selected medical skin image of the plurality ofmedical skin images and (y) an extracted at least one respectivehuman-perceivable feature included in each medical skin image of theplurality of medical skin images other than the selected medical skinimage; (iii) gathering the determined substantial correspondences forthe extracted human-perceivable feature included in the border regionsegment of the selected medical skin image; (iv) generating dataindicative of a border region-overlap status of the selected medicalskin image, the data generated at least partially in response to thedetermined substantial correspondences; (v) adding the data indicativeof the determined border region-overlap status for the border regionsegment of the selected medical skin image to an omitted-coverage list;(vi) iteratively designating a next medical skin image from a pluralityof medical skin images as the selected medical skin image until eachmedical skin image of the plurality of medical skin images has beendesignated; (vii) processing of each of the iteratively designated nextmedical skin images, the processing including operations (ii), (iii),(iv), and (v); (viii) identifying a particular portion of the skinsurface as likely not included in the plurality of medical skin images(hereafter “possible non-imaged portion of the skin”), the identifyingthe possible non-imaged portion of the skin at least partially based onthe omitted-coverage list; and (ix) outputting user-assistanceinformation at least partially based on the identified possiblenon-imaged portion of the skin.
 26. The computer program product ofclaim 25, wherein the outputting user-assistance information includes:outputting user-assistance information in substantially real time and atleast partially based on the identified possible non-imaged portion ofthe skin.
 27. The computer program product of claim 25, wherein theprocess further includes: receiving the plurality of medical skinimages.
 28. The computer program product of claim 25, wherein theprocess further includes: detecting the border region segment of amedical skin image of the plurality of medical skin images.
 29. Thecomputer program product of claim 25, wherein the process furtherincludes: displaying the user-assistance information.
 30. The computerprogram product of claim 25, wherein the process further includes:maintaining the user-assistance information in computer-readable storagemedia.
 31. The computer program product of claim 25, wherein thenon-transitory computer-readable medium includes a tangiblecomputer-readable medium.
 32. The computer program product of claim 25,wherein the non-transitory computer-readable medium includescommunications media.
 33. A system comprising: (a) means for extractingat least one respective human-perceivable feature included in eachmedical image of a plurality of medical images of the skin of anindividual human (hereafter “medical skin images”), the each medicalimage of the plurality of medical skin images includes a respectiveportion of a region of interest of a surface of the skin of theindividual human, and was acquired by a handheld digital imageacquisition device; (b) means for determining a substantialcorrespondence between (x) an extracted human-perceivable featureincluded in a border region segment of a selected medical skin image ofthe plurality of medical skin images and (y) an extracted at least onerespective human-perceivable feature included in each medical skin imageof the plurality of medical skin images other than the selected medicalskin image; (c) means for gathering the determined substantialcorrespondences for the extracted human-perceivable feature included inthe border region segment of the selected medical skin image; (d) meansfor generating data indicative of a border region-overlap status of theselected medical skin image, the data generated at least partially inresponse to the determined substantial correspondences; (e) means foradding the data indicative of the determined border region-overlapstatus for the border region segment of the selected medical skin imageto an omitted-coverage list; (f) means for iteratively designating anext medical skin image from the plurality of medical skin images as theselected medical skin image until each medical skin image of theplurality of medical skin images has been designated; (g) means forinitiating a processing of each of the iteratively designated nextmedical skin images, the processing including operations at means (b),(c), (d), and (e); (h) means for identifying a particular portion of theskin surface as likely not included in the plurality of medical skinimages (hereafter “possible non-imaged portion of the skin”), theidentifying the possible non-imaged portion of the skin at leastpartially based on the omitted-coverage list; and (i) means foroutputting user-assistance information at least partially based on theidentified possible non-imaged portion of the skin.
 34. The system ofclaim 33, wherein the means for outputting user-assistance informationincludes: means for outputting user-assistance information insubstantially real-time and at least partially based on the identifiedpossible non-imaged portion of the skin.